How to Find the Perfect Custom Software Development Team
Daria Lymanska
CEO & Founder
June 4, 2024
2
min read
Evolving companies regularly look for new ways to bypass competitors in today's dynamic world. At the same time, software development for business is one of the most effective strategies. External expertise enables them to achieve higher levels of efficiency, innovation, and financial savings. However, finding the perfect outsourced web development team with all the individual needs can be tricky. Today, we will share essential tips on this topic with you.
It should be noted that the demand for hiring software development team has increased significantly in recent years. According to Statista, global income from IT outsourcing will continue its rapid growth for the next eight years. The following figure shows the projected increase in its revenues worldwide:
Size of the managed service market worldwide in 2023 with forecast to 2032
How to Find the Best Outsourced Development Team
As already noted, the process of finding the perfect web outsourcing team is in most cases an absolutely daunting task, but we are ready to share with you some effective methods that will simplify this process:
Internet search: Look for companies with high ratings and many positive reviews directly through search engines (Google and so on). It is worth starting with the main search queries and gradually detailing them using filters or keywords. It is also recommended to browse companies' websites, articles, and blogs directly to be more guided in their expertise.
Recommendations: One proven and reliable way to find real pros is to seek advice or recommendations from your colleagues, employees, or business partners. If your acquaintances already dared to outsource dedicated software development teams, you can directly ask people from your professional network who they can recommend and for what reasons.
Implemented cases and portfolios: Carefully review the portfolios and cases of your potential partner. This will help you analyze the outcome of their previous projects and determine if their style and approach meet your individual requirements. It is also necessary to pay attention to those projects that are similar in structure and concept to yours.
Social networks and professional communities: Social networks and professional communities (like LinkedIn) are great options for finding reputable, highly specialized outsourcing service providers and analyzing customer reviews. They are also an excellent way to get more information about your contractor and its professional connections.
Freelance platforms: Upwork, Toptal, and Freelancer are useful platforms for finding and communicating with experienced specialized specialists. These platforms also provide access to a vast database of freelancer profiles, ratings, and portfolios, which will help you get a complete picture of their professional competence.
Events and conferences on professional topics: By attending various specialized events, you can expand your network of social contacts. In addition, you can personally communicate with potential partners, ask them questions that interest you, and make more or less objective impressions of them.
What Should You Look for When Searching for an Outsourced Development Team?
Clear positioning
Each company excels in a specific area, focusing on a single or a few related directions, such as mobile and web development. This specialization ensures their expertise and quality in these particular fields. It's important to note that the best outsourcers refrain from attempting to offer design, coding, and a myriad of other services simultaneously.
The presence of the grads and their description
If an outsourcer sells the services of Junior, Middle, and Senior specialists, there should be clear descriptions of what they can do and at what level.
Consent to interview
Even if you plan to interview only some experts, asking the service provider representative if they are open to interviews is beneficial. This step lets you feel more involved in the selection process and ensures that the outsourcing company is transparent.
Cases
The cases may be so problematic that the outsourcer projects for other companies are under NDA, and details cannot be disclosed. Therefore, cases can be impersonal without specifying specific customers.
How Do You Evaluate an Outsourced Development Team?
It is worth paying attention to several main aspects to make an informed, balanced, and final decision regarding outsourcing software development to a dedicated team. Undoubtedly, the portfolio and successful cases should be reviewed first to evaluate their previous projects.
After that, assess the technical skills and ability to work with the tools and technologies necessary for your project. For practical analysis, conduct technical interviews or ask for a test assignment to verify their qualifications.
Pay attention to the level of communication. The remote development team should respond quickly to your requests, clearly formulate their thoughts, and be ready for regular reports.
Compare the cost of services, considering the value for money your future partners ask. No one will argue that when you hire software development team, the cheapest option is not always the best, so it is worth assessing the cost of services in the context of the overall quality of work and the results you will receive.
Clarify the guarantees and level of support after the project is completed when you try to find outsourcing companies. For example, reliable contractors usually offer a specific warranty period and post-project support to ensure the smooth operation of the product.
Finally, assess whether the outsourcer's culture and values match yours. This may not be the most pragmatic metric, but it is equally important during hiring remote outsource developer. Specifically, your contractor must share your values and be prepared to work according to your standards and requirements. This will ensure harmonious cooperation when you hire outsourcing team.
Software Development Outsourcing with Darly Solutions
Choosing Darly Solutions for software outsourcing development gives you several advantages that help solve problems of any complexity efficiently and without compromising your budget. Regardless of the specifics of your project, we will provide you with the necessary resources and support, allowing you to focus on the main thing – ensuring the prosperity of your business.
Access to new resources for development and support:
When you hire a remote outsource developer Darly Solutions, you get seamless access to talents with experience in new, improved, and specialized tools and technologies.
Cost-effective development:
Darly Solutions offers affordable prices for programming and support services. Moreover, technical support is included in the service package for a certain period, contributing to reduced overall costs.
Clear deadlines for the project:
At the stage of forming the technical assignment, Darly Solutions provides you with clear deadlines for the project implementation. Strict adherence to the project terms eliminates the human factor's influence and ensures stability in achieving goals.
Reliable forecasts and adequate perception of the project:
As your digital partner in outsourcing software development for startups, we always guarantee reliable forecasting of software performance, ensuring a clear idea of the results and investments.
Competent optimization of any processes:
Systematic optimization of software, increasing its stability, and reducing the likelihood of errors allow us to meet pre-defined standards and business goals.
Conclusion
The aforementioned insights about hiring outsourcing team will allow you to make the right choice and find the best one, considering all the features and details of your project. However, you should remember that choosing a software development company as the right and reliable partner is more than just the immediate outsourcing benefits of high-quality and prompt task fulfillment – it's more about laying a solid foundation for future success.
Why should I consider outsourcing my software development?
Outsourcing can increase efficiency, drive innovation, and reduce costs by leveraging external expertise without the need for in-house resources.
What factors should I consider when evaluating a potential outsourcing partner?
Key factors include the team's technical skills, communication abilities, previous case studies, cost of services, and cultural alignment with your company.
Are freelance platforms a good place to find development teams?
Yes, platforms like Upwork, Toptal, and Freelancer offer access to experienced professionals with verified ratings and portfolios.
Why is Darly Solutions a good choice for software outsourcing?
We at Darly Solutions provide access to expert talent, cost-effective development, clear project deadlines, and reliable forecasting.
In today's world of IT technologies, cooperation with Ukrainian developers is becoming more and more relevant and promising. Ukraine is ranked as one of the world's top IT service providers and continues to hold that position.
Ukrainian IT market overview
Today, the Ukrainian IT market has positive growth dynamics, as Ukraine is a more favorable center of cooperation than other countries. Why is this so? It is due to our specialists' high level of education, scientific potential, the country's proximity to the European market, and favorable tax conditions. The close geographical location to Europe also ensures faster and more efficient communication between clients and developers. All this makes it possible to double Ukraine's export revenues in the next 4 years.
Currently, more than 200,000 Ukrainian developers work in the international market. That demonstrates the high level of qualification and professionalism of IT specialists who successfully work on projects of any scale and complexity.
In 2021-2022, the IT industry grew by 36%, from $5 billion to $6.8 billion in exports. Over the past three years, these figures have almost doubled, and the growth trend is quite stable. Despite the war and issues many IT companies face nowadays, the IT sector is still a driving force in the Ukrainian economy and continues to develop.
The majority of IT companies today work remotely. But this does not prevent participants in the development process from creating digital products, being in touch with the client, and providing timely updates on the work done. During the full-scale invasion of the aggressor country, all Ukrainian companies have adapted to the new reality and are ready for force-majeure situations at any level.
Our company did not disrupt any project over the past year and delivered all developed products to each customer. Moreover, our practical work resulted in the support of foreign customers who want to cooperate only with Ukrainian companies on convenient terms.
Development tasks that Ukrainian developers solve
Ukrainian developers today are among the most in-demand in the world. Through continuous development and training, top-notch IT specialists contribute to developing international products and participate in their launch and maintenance. They successfully solve many development tasks and problems, including:
Complex technical projects
Ukrainian developers have high technical expertise and can implement projects of any complexity. They use the most advanced technologies and programming languages, such as Java, Python, Ruby, JavaScript, etc.
Mobile application development
A significant amount of experience is available among Ukrainian developers in developing mobile applications for iOS and Android platforms using React Native, Ionic, and other technologies. They know how to create intuitive, user-friendly interfaces that satisfy users' needs. They also specialize in developing cross-platform applications that run on multiple operating systems, which can significantly speed up the development process and reduce project costs.
E-commerce platform development
Ukrainian developers also have considerable experience in developing online stores and e-commerce platforms. They are familiar with major CMS systems such as Magento, Shopify, and WooCommerce.
Software development
It is well known that Ukrainian developers create high-quality software. They know how to write code that will work quickly, efficiently, and reliably. They also have experience in various areas, such as web development, mobile development, artificial intelligence, and more. Ukrainian developers often use modern technologies and development methods such as Agile, Scrum, and DevOps to ensure high quality and fast development time.
Integration and maintenance
Besides developing new software, Ukrainian developers integrate it with existing systems and maintain them. They are ready to solve problems during the operation and ensure the smooth operation of the applications.
Cybersecurity
Ukrainian developers actively work in cybersecurity, providing reliable protection of information and data. They know how to protect applications from threats like hacker attacks, viruses, and other malware. And also use modern technologies and methods such as data protection, encryption, and authentication to keep software secure.
Advantages of cooperation with Ukrainian developers
Cooperation with Ukrainian developers today is one of the most advantageous options for companies looking for reliable and experienced IT specialists. Ukraine is one of the world's leaders in the IT services market, thanks to its talented and highly qualified developers capable of fulfilling tasks of any complexity.
One of the main advantages of working with Ukrainian developers is the high quality of their work. Ukrainian developers have an extensive experience in various fields of IT. They follow the latest trends and use the most advanced technologies. Due to this, they can realize tasks of any complexity, including creating complex websites, mobile applications, software development, and much more.
In addition, Ukrainian developers are known for their speed and efficiency. They strive to complete their projects on time without compromising the quality of their work. Ukrainian IT companies are also ready to provide flexible working conditions, including working in different time zones, which makes cooperation with them even more convenient and effective.
One more advantage of cooperation with Ukrainian developers is their price competitiveness. Ukraine offers more favorable conditions for cooperation than other countries while maintaining a high quality of work and professionalism. That allows companies to save on costs without losing quality.
Flexible cooperation conditions are another advantage of Ukrainian developers. Many of them work remotely, which makes their services more flexible and accessible to clients from all over the world. That reduces the cost of organizing work with remote teams and the time required to find the right specialists. In addition, even remote communication with Ukrainian developers allows you to respond quickly to changes in the project and solve any problems that may arise. Also, communication with Ukrainian developers is in English, which facilitates interaction with customers from around the world.
Summary
Ukraine is one of Europe's largest exporters of IT services, with an excellent knowledge base, great motivation, and great opportunities. Despite the Russian invasion, Ukrainian IT companies continue to provide quality services, support the economy, and maintain a high rate of development and continuous growth.
Cooperation with the Ukrainian company is not only a guarantee of quality work but also support for Ukrainian businesses and Ukraine as a whole. Numerous IT companies survived difficult times and are gaining momentum in their activities due to the trust of international customers and the continuous work of the development team.
The implementation of artificial intelligence (AI) and machine learning (ML) has the potential to turn the healthcare industry upside down. And this global transformation is already beginning. Innovative technologies are being used in diagnostics and treatment. They are influencing pharmaceuticals, research work, and other aspects of medical practice.
Analysts at Global Market Insights have calculated that the AI market in healthcare is valued at $18.7 billion. However, by 2032, the situation will change. According to forecasts, its size will exceed $317 billion.
Considering this trend, we find it appropriate to explore the prospects that AI and the technologies based on it offer to medical professionals worldwide. We will also focus on the near future of AI-based medical solutions and discuss examples of digital products that are already available to specialists.
What Are Machine Learning Healthcare Projects?
Machine learning projects in the medical field involve the use of ML algorithms and models to perform various tasks for healthcare workers. These include:
data collection and analysis;
predicting the condition of patients and treatment outcomes;
making decisions about the appropriateness of certain prescriptions, and more.
The effectiveness of using AI and ML in healthcare is confirmed by numerous specialized studies. Below are some examples:
The Houston Method Research Institute used an AI-based tool for diagnostic purposes. Specifically, it was used to detect malignant breast tumors. The results shocked scientists. The system demonstrated a disease detection accuracy approaching 99%. Moreover, AI was able to analyze mammograms 30 times faster than humans.
The Nationwide Korean Cohort Study focused on researching the effectiveness of predicting infectious disease outcomes using machine learning. The results showed that the accuracy of the applied ML model was over 90%.
Scientists from Indiana University and Purdue University in Indianapolis developed an ML-powered system to predict the outcome of acute myeloid leukemia. The results of the model's tests demonstrated that it could predict remission with 100% accuracy. The likelihood of recurrence was correctly identified in 90% of cases.
Researchers at BMJ Health & Care Informatics developed and tested a machine learning model for detecting NASH (non-alcoholic steatohepatitis). This disease is difficult to diagnose. However, the use of ML contributes to more accurate screening of NASH and allows for the timely application of effective treatments.
All of these statistics confirm the vast potential of machine learning in healthcare projects. So, what is this technology most often used for?
Popular Use Cases of AI Projects in Healthcare
According to Morgan Stanley Research, 94% of respondents (medical companies) reported using AI or ML in their practice.
Let’s take a look at which aspects of healthcare these technologies can optimize.
1. Pathology Detection
Machine learning models can be used to analyze various types of images. The goal is to recognize pathological conditions.
For example, they can be used to diagnose cancer, tuberculosis, and other infections.
How does this work in practice? Here are several examples of using ML in the field of pathology detection:
A machine learning-based program analyzes tissue samples and helps identify malignant growths.
ML algorithms recognize tuberculosis by examining sputum samples from an infected person.
ML-based systems help differentiate between benign and malignant tumors.
An example of such software is AIM-PD-L1: an AI and ML-based tool that detects PD-L1. This protein is formed as a result of cancer cell development. Research on this solution showed that its results closely align with human diagnostics. Thus, the tool can be useful in identifying pathology.
Another solution from the same developer, PathAI, is the PathExplore panel for histopathological features. It can analyze tissue images at the pixel level. This allows it to examine millions of cells and accurately identify malignant ones.
2. Medical Imaging and Diagnostics
Healthcare machine-learning projects often use innovative technologies to analyze various images. These include CT scans, MRIs, mammograms, X-rays, and more.
Here’s how machine learning models can be used in diagnostics based on visual data:
An ML-based system can analyze CT scan results and, with a high degree of accuracy, identify malignant tumors.
Similarly, such platforms can diagnose ischemic strokes, such as hemorrhage, based on brain MRIs.
Specialized ML-based tools allow for retina scans. This helps in the early detection of blindness due to diabetes, specifically diabetic retinopathy.
There are many similar solutions available on the market. Among them are Viz.ai and InnerEye.
The first, Viz.ai, is a care coordination system based on AI. It allows for automate detection of many diseases, including vascular pathologies.
The second, InnerEye, is a solution from Microsoft that significantly speeds up work with patient images. For example, with this platform, doctors can accurately differentiate between healthy and cancerous cells. It also accelerates the start of treatment by 13 times.
3. Personalized Medicine
Each patient is unique due to the following characteristics:
genetic predisposition;
medical history;
lifestyle;
comorbid health issues, and more.
Machine learning-based platforms are able to take all these factors into account when selecting treatment methods.
Here’s how this can work in practice:
ML models analyze genomic data and recommend individualized treatment methods for oncological diseases.
Thanks to predictive analytics, AI-based tools can adjust insulin dosage. This is possible through constant monitoring of its level in the patient.
Machine learning algorithms help choose the optimal antidepressant based on the patient's psychological state and genetic predispositions.
As an example, let's look at IBM Watson for Oncology. This is a machine learning-based system that considers many factors when recommending cancer treatments. These include the compatibility of prescribed medications, possible side effects, and the effectiveness of treatment in each specific case. As a result, the system provides healthcare professionals with several therapy options from which they can choose the most optimal.
4. Drug Discovery Process
The use of ML can accelerate the invention of new pharmaceuticals. Specialized systems show excellent results in discovering the medicinal properties of various substances. They can also analyze the interactions of drug components and optimize clinical trials.
AI in healthcare projects can be used for this purpose as follows:
ML models accelerate the search for antibiotics and antiviral drugs.
AI-based modeling helps reduce the number of failed clinical trials, thus saving time and resources.
Machine learning algorithms can analyze the structure of substances, assisting in the development of new drugs.
A notable example of using AI and ML in creating new drugs is AlphaFold by DeepMind. This tool is designed to determine the structure of proteins, which are the foundation of biological processes in every living organism. Currently, the platform is successfully used for:
fighting malaria;
searching for a treatment for Parkinson's disease;
counteracting bacteria resistant to existing drugs.
5. Epidemic Prediction
One of the capabilities of ML models is analyzing patterns and making predictions about outbreaks of various diseases.
Here are some examples of using ML-powered solutions:
Such systems can predict global pandemics. To do this, they analyze data on population movement and disease statistics.
ML algorithms track seasonal disease spikes, such as the flu.
“Smart” platforms can predict outbreaks of specific diseases in high-risk areas. For example, they can forecast cases of malaria or dengue fever.
EPIWATCH is one of the leading examples of such platforms. This tool uses artificial intelligence to predict epidemics that could reach a global scale. The system collects and processes extensive infectious disease data in real time. It has proven effective in providing early warnings about potential pandemics.
6. Remote Patient Monitoring
In recent years, IoT (Internet of Things) devices have become widely used in medicine. These are objects equipped with sensors that can collect and transmit data wirelessly without human intervention.
According to Yahoo!Finance, the IoT market in healthcare, was valued at $58.8 billion in 2024, and by 2032, it is expected to exceed $305.5 billion.
This situation is explained by the fact that AI and ML enhance the efficiency of wearable devices and health monitoring systems in general.
The use of ML in remote monitoring includes the following cases:
Smartwatches can track irregular heart rhythms and detect instances of sleep apnea.
ML models can analyze ECG data in real time. Based on the obtained data, they can predict a heart attack.
AI-based inhalers can track the patient’s readings and warn about an asthma attack.
There are many such solutions on the market. These include popular devices like the Apple Watch and Fitbit. These smart bracelets can monitor heart rhythms and detect uncontrolled breathing stops.
There are also more complex systems available to healthcare professionals. For example, SafeBeing from Somatix. Thanks to wearable devices, this platform responds to patient gestures and draws conclusions about their health condition.
7. Virtual Assistants
Not everyone can visit a medical facility in a timely manner. Moreover, many people need assistance and support after being discharged from the hospital. AI handles these challenges effectively. Developers are actively creating digital assistants with integrated ML algorithms. These assistants are capable of providing first-aid and consulting patients after treatment.
What can such tools do?
These platforms help assess health status independently and suggest possible diseases.
Smart chatbots help schedule doctor visits, remind patients to take medications, and more.
Virtual assistants help monitor the progress of chronic diseases.
There are many such solutions available to patients. Let’s look at the features of Ada Health as an example. This platform helps assess symptoms and provide preliminary diagnoses using machine learning algorithms. It can:
track changes in the body over time;
provide recommendations regarding treatment and a healthy lifestyle.
8. Psychiatric Assistance
ML algorithms help diagnose and treat various psychiatric disorders, including those used in the fight against depression and anxiety.
Practical examples of ML usage in psychiatry:
Intelligent chatbots can mimic real-world conversations. They can answer patients' questions and provide recommendations.
ML models can analyze user behavior on social media and detect suicidal tendencies.
These digital solutions can analyze human speech and identify early signs of Alzheimer’s disease.
Woebot is a smart chatbot that helps people with mental health disorders. It can assess a user’s mood and emotions. Among its functions are conducting conversations with patients and providing personalized strategies for coping with difficulties.
9. Robotic Surgery
Just imagine. Surgeons no longer need to be in the operating room. All procedures are performed by a robot. Sounds like a scene from a sci-fi movie? Nevertheless, this is our reality. Developers have already created robotic systems based on AI that enhance the accuracy of surgical interventions and reduce rehabilitation time.
What can such software do?
Smart surgical systems can perform minimally invasive surgeries.
AI-based software shows excellent results in neurosurgery and orthopedics.
ML models predict potential surgical risks and possible complications.
Here, we cannot fail to mention the famous Da Vinci surgical robot created by Intuitive Surgical. This robotic system offers medical professionals incredible possibilities in the field of minimally invasive surgery. Its features include fluorescence visualization, integrated table movement, a vision cart, and more. This allows for precise and effective surgical interventions.
10. Automation of Administrative Tasks
Routine tasks such as organizing document flow or billing require a lot of time, diverting medical staff from their primary duties — treating patients. The implementation of machine learning-based software allows automation of these processes, reducing the time spent by medical personnel.
AI-powered systems are handling numerous administrative tasks:
Platforms based on NLP can extract data from medical records and update patient electronic charts.
ML algorithms analyze insurance cases, minimizing fraudulent claims.
Smart scheduling systems efficiently manage hospital resources.
An example of such software is the Optum system. It offers numerous solutions for the healthcare business, including a platform for Revenue Cycle Management. Its capabilities include billing, increasing revenue efficiency, medical coding, and documentation.
Benefits of Machine Learning for Healthcare Analytics Projects
The use of ML models in healthcare allows for the analysis of large amounts of medical data. Furthermore, such models are continuously trained and improved. The implementation of tools based on these models brings a number of benefits to both medical professionals and patients:
Early Disease Diagnosis
Identifying serious diseases at early stages reduces mortality, improves the quality of life for patients, and increases the likelihood of full recovery or sustained remission. For medical institutions, this helps reduce their expenses and saves time.
ML models excel at early diagnosis. They analyze medical images, test results, and patient medical histories. They then track patterns and detect even the slightest deviations from the norm.
Improvement in Patient Care Quality
This is facilitated by AI-based digital solutions for personalized care, virtual assistants, and chatbots. They help maintain a person's health outside of the hospital, for instance, after discharge or before visiting a specialist.
At the same time, such platforms help reduce the workload on medical institutions. They can provide the patient with an initial consultation and allow medical professionals to remotely monitor the patient's condition.
Development of the Pharmaceutical Industry
Innovative technologies allow for faster development of new medications. This is a step toward effectively combating various diseases. This is particularly relevant during global epidemics.
Cost Reduction
ML automates many processes in healthcare, from documentation management in clinics to diagnostics and treatment prescriptions. Additionally, the use of smart technologies helps reduce human errors and allows for some patients to switch to home care. As a result, medical institutions can increase the number of patients served and their profits.
Improvement in Treatment Effectiveness
In medicine, predictive models are used, which are trained on large sets of historical patient data. Such models can predict:
the likelihood of recurrence;
the need for hospitalization;
the tendency for the disease to progress.
Medical professionals can use all this data to adjust the prescribed treatment to improve its effectiveness.
Key Challenges in Healthcare Machine Learning Projects
The implementation of machine learning in healthcare projects opens up many opportunities for the industry. We have already seen this today. However, alongside numerous advantages, some challenges may arise for innovators.
Security of Confidential Data
The digitalization of healthcare has led to a particularly sharp issue. We mean the preservation of medical confidentiality and the privacy of patient data. The use of virtual tools implies entering personal information into the system, which increases the risk of data leakage.
To mitigate these risks, maximum anonymity should be maintained. For example, financial and insurance data, as well as the patient's address, should not be included. It is also important to implement reliable data encryption methods and threat notification mechanisms on the platforms.
Quality of Data for Model Training
The effectiveness of ML models depends on the data input into the system. Inaccurate input data can lead to incorrect diagnoses, wrong treatments, and even death.
To prevent this problem, machine learning software should be used under the supervision of highly qualified medical staff.
Skepticism of Healthcare Professionals and Patients
Since machine learning projects in the medical field are still in the early stages of gaining ground, many doctors and patients are not fully confident in its capabilities. The main concerns include inaccurate diagnostics and the complete replacement of human involvement in medical practice.
To build trust, continuous training for healthcare professionals and patients is necessary. It is also important to notify people about the chosen treatment methods.
As for the complete replacement of human labor, this is highly questionable. Scientists believe that innovative technology will, in fact, expand the role of healthcare professionals. Their duties will include overseeing the operation of ML models and interpreting their results.
Difficulty of Integration with Existing Software
To ensure the smooth operation of medical institutions, new software products need to be seamlessly integrated into the existing infrastructure. The task becomes more complex because clinics may be using outdated systems that are not compatible with new technologies.
To solve this problem, investment in qualified IT personnel and gradual replacement of old software with new ones is necessary.
Technologies Used in Machine Learning Projects in Healthcare
Such high efficiency in AI projects in healthcare is achieved thanks to the wide range of technologies used in specialized software. Let's look at the main ones.
Computer Vision
This is the ability of a machine to understand and interpret visual information from the external world. In healthcare, it is used for analyzing medical images for subsequent diagnosis and treatment.
Examples of use:
detection of tumors in X-rays, CT scans, or MRIs;
analysis of biopsy results to identify malignant formations.
Robotic Process Automation (RPA)
This involves using bots (software robots) to perform repetitive tasks. In medicine, this technology is applied to automate administrative processes.
Examples of use:
processing insurance claims;
billing;
inputting data into electronic patient records.
Logistic Regression
This is a statistical machine learning algorithm that is effective for predicting the probability of disease and classifying ailments.
Examples of use:
assessing the risk of developing diabetes;
determining the likelihood of cardiovascular diseases.
Support Vector Machines (SVM)
This is a supervised machine learning algorithm that is best suited for classification, i.e., separating data into different categories. It is used in medicine for diagnostic purposes.
Examples of use:
differentiating between benign and malignant tumor cells based on biopsy data;
classifying genes to identify genetic disorders.
Natural Language Processing (NLP)
This is a field of artificial intelligence that enables computers to understand, interpret, and generate human language. It is used to process medical text, such as doctor’s notes or specialized literature.
Examples of use:
analyzing electronic medical records to extract patient data;
virtual assistants and chatbots to assist patients outside medical facilities.
Large Language Models (LLM)
These are a specific type of machine learning models trained on large datasets. Their capabilities include understanding and generating human-like language.
Examples of use:
answering complex medical questions;
automating clinical documentation.
Deep Learning (DL)
A subset of machine learning that uses neural networks with multiple layers to perform tasks. It is applicable for image recognition and speech processing. It is widely used in medical imaging, as well as in fields such as genomics and pharmaceuticals.
Examples of use:
developing new medications;
diagnosing diseases based on visual data.
Reinforcement Learning (RL)
A type of machine learning where an agent learns by interacting with its environment, in other words, through trial and error. This technology helps optimize the effectiveness of treatment strategies.
Examples of use:
robotic surgical systems;
personalized treatment for various diseases.
The powerful potential of AI-based technologies suggests that the future of healthcare lies in them.
Future Trends in AI and Machine Learning in Healthcare Projects
It is predicted that in the coming years, AI and machine learning will continue to strengthen their position in healthcare. This is facilitated by:
better awareness of these technologies among doctors and patients;
an increase in the number of developers capable of creating and integrating innovative systems;
a growing demand for skilled healthcare services and medications.
What can we expect in the near future?
Transformation of Primary Healthcare
AI and machine learning systems will take on more responsibility during a patient's initial visit to the doctor. They will classify patients based on their risk level, using examination results. Patients with a low probability of illness will be notified immediately. Those with a high risk will be referred to specialists.
This will reduce the waiting time for referrals and ease the burden on specialists.
Improvement of Healthcare Accessibility
According to the International Labour Organization, 56% of people living in rural areas have no access to healthcare. In cities, the situation is better but still concerning, with 22% of the population unable to access medical services.
AI and machine learning have the potential to fundamentally change this situation. This will be possible through telemedicine and mobile health services.
Focus on Data Security
AI system developers understand the importance of ensuring data security in healthcare. The HIPAA Journal states that in 2023, over 133 million medical records were exposed due to data breaches. This means the problem is becoming global in scale.
As a result, IT specialists will work on enhancing the reliability of the security measures being implemented.
Progress in Early Disease Detection
Modern intelligent software is capable of recognizing symptoms at the very early stages of disease development. However, in the near future, AI capabilities will go even further. The first steps in this direction are already being taken. An example is the Sybil tool developed by scientists from the Massachusetts Institute of Technology. It can predict the development of lung cancer within a year with 94% accuracy.
This is a huge breakthrough in healthcare. It has the potential to save millions of lives.
Emphasis on Personalized Treatment Plans
Doctors will increasingly move away from general prescriptions that do not account for the specific characteristics of individual patients. AI systems will be used to analyze medical histories, genetics, and other factors. Based on this analysis, personalized treatment methods will be selected.
This approach is particularly relevant for treating complex diseases such as cancer.
Darly Solutions Case Studies
Finally, we would like to share the experience of the Darly Solutions team. Our custom healthcare software development company has implemented many successful AI-powered projects for healthcare.
A company approached us with concerns about patient safety during the diagnosis of infectious diseases. They decided to rely on AI and machine learning for the accuracy and safety of their research.
The Darly Solutions development team created a platform for the client that can achieve 99.9% accuracy in clinical diagnostics. To achieve such impressive results, we used the following technology stack:
Python for machine learning and data analytics;
JavaScript and React for creating an intuitive user interface;
WordPress for backend development.
We successfully implemented predictive tools, high-quality data visualization, and a user-centered UI/UX design in the diagnostic solution. As a result of our collaboration, the client’s goals were met. The company received a flexible, scalable, and highly efficient system.
Conclusion
It can be confidently stated that machine learning projects in the medical field are the future of global healthcare. Intelligent solutions have the potential to revolutionize disease diagnosis and treatment, patient care, and drug development.
Do you want to follow the latest trends and provide the highest quality services? Now is the perfect time to find an expert team to develop an AI and machine learning-based medical application.
The Darly Solutions team is ready to assist you with this! Contact our manager to discuss the project details and receive a digital solution that will exceed all your expectations.
Many of you have heard about Artificial Intelligence from OpenAI - ChatGPT. No wonder because all the social networks and the Internet, in general, are full of headlines about a newfangled tool that conquered the whole world with its capabilities. Before we give a more detailed description of this tool, let's go over the basics of this technological wonder.
To get started with the chat, you need to register in the system. The process is similar to registration in social networks and takes little time. And then, you just need to enter a request on the principle of communication with a live person. In fact, he can answer any of your questions, but keep in mind that the request must be accurate and precise. The robot will catch the context of the request and give you a text response.
The model uses a neural network architecture called a transformer, trained on a large corpus of text data. The transformer learns patterns and connections between words and phrases in the text data, which allows it to generate new connected and grammatically correct text.
ChatGPT is changing the world by making communication more accessible and efficient. Using natural language processing, it can understand language much higher than traditional methods. This means that ChatGPT-based chatbots can respond to users more naturally and human-likely.
ChatGPT areas of opportunity
OpenAi has transformed the digital world with ChatGPT. With it comes more and more opportunities for developers, marketers and designers, business owners, office workers, and others. The ability of AI chatbots to understand our language makes interacting with technology more accessible.
Let's look at ChatGPT areas where it can be most helpful:
Blogging
If you have a blog or plan to create one, this tool is handy. It helps you generate blog topics, rubrics, and texts for them. We recommend making additional edits to the generated texts to add individuality and better promotion in search engines.
Content marketing
Marketers can safely draw ideas and inspiration here with a well-formulated query to the system. This is not a panacea for all marketer's problems but a great helper for creating creative content or themes. It's essential to use GPT-generated content as a starting point and to carefully review and edit the text to ensure that it meets your standards and accurately represents your brand or message.
Chatbots
When a business needs to communicate with customers or effectively put the process of ordering goods or services - chatbots are the perfect solution to close this issue. Since chatbots and ChatGPT are identical, you'll have no problem incorporating them into your business. And the GPT tool will compose questions and answers for prospective conversations with your customer.
Trading
It can collect market data to identify patterns and predict future market trends, analyze social media and news articles to determine market sentiment and identify potential risks in the market, which can be used to make strategic decisions to minimize losses and maximize profits.
Code writing
In addition to plain text, this chatroom can even write code for a program. Users have already tested it to write code for Angular, Python, and other developing technologies. And HTML/CSS is a piece of cake.
Incredible things that you can do with the help of ChatGPT
ChatGPT has revolutionized research and development with its idea generation, data analysis, and simulation creation capabilities. It can generate natural text that sounds like it is spoken by a human, providing personalized support in various sectors, from healthcare to customer service. In addition to these powerful features, ChatGPT offers excellent benefits for market research and automating tasks such as content creation or customer interaction on social media sites. Pretty impressive right?
The basic list of what you can create with it includes the following items:
Text Generation
ChatGPT can generate human-like text of any complexity. It can be used to create creative works, scripts, articles, stories, poems, and other forms of text content.
Translation to other languages
Just enter the desired text and specify a request for its translation with the specific parameters, if any, for translation.
Text Summarization
ChatGPT can summarize significant lengthy texts into shorter versions explaining the main points and thoughts.
Ending a text
If you have a beginning of a text or a code, you can complete it in your desired direction by specifying this in the chat request. Be as specific as possible in your request, so the answer matches the expected result.
Answering questions
ChatGPT can answer questions based on the context you set, which is helpful for customer service chatbots. Also, it provides information on a wide range of topics.
So what's the bottom line: replace or implement?
In recent months, discussions about ChatGPT taking over all spheres and professions, which are somehow related to the content, have been raging on the Web. Such drastic changes will certainly not happen soon, and here's why:
ChatGPT can be great for dealing with fundamental customer service issues and providing quick information, but more complex or sensitive issues require human involvement. Customers want a personalized experience, so real people answering their questions are still needed.
ChatGPT can't provide a different level of empathy, judgment, and problem-solving than a human customer service representative. In addition, its responses are limited to pre-programmed scripts that need to be more flexible for different customer needs rather than people who can offer more adaptive solutions.
ChatGPT can help improve customer service, but it will never replace the value of human interaction and expertise.
As AI continues to evolve, there will be an increasing need for individuals who can design, develop, and maintain these systems. AI also creates new job opportunities in data science, machine learning, and robotics. These jobs require specialized skills and knowledge that are in high demand. People may need to adapt to new roles that require more advanced skills, such as managing and maintaining AI systems.
That is why it makes sense to talk not about replacing the central employees with a chat room but introducing AI technology into the company. It should not be a substitute for specialists, but a technical addition, which will increase the work process's efficiency and help you find new ideas and rely on when making business decisions. Moreover, the chat cannot exist separately from the person because its system needs to be updated, cleaned, and worked with when necessary. There is a possibility of creating a collaboration of human and AI that significantly increases the productivity of any company.
Summary
ChatGPT is a powerful and unique tool that can be incredibly useful in many contexts. However, as with any technology, it is essential to use it responsibly and to be critical of its limitations and potential biases. It has already brought significant benefits, such as increased efficiency and productivity, improved decision-making, and quality of life.
In any case, we should not rely solely on the work of Artificial Intelligence. It is important to critically evaluate its results and format it to the necessary level. After all, no one has yet been able to recreate the human mind. So use this tool wisely, maximize work quality, and simplify your workflow. ChatGPT handles this perfectly.
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