Is AI already affecting healthcare software development, or is it just a well-played marketing stunt? Below, you’ll find answers to the hottest questions on how AI and ML keep transforming the healthcare industry.
Will AI enhance remote patient monitoring? Is it possible to detect cancer and other skin diseases with computer vision? Are we just about to overcome medical staff shortages globally with AI? And finally, is there a possibility for quick, efficient, and ethical drug development in the near future? Read on and find answers to these and many more questions.
Telemedicine
Telemedicine is a broad umbrella term covering the remote delivery of healthcare services using telecommunications technologies. It is expected to reach around a $160 billion market value, with projections to go as high as $709 billion by 2034, according to Precedence Research. AI has a strong influence on the overall development of telemedicine, including improved virtual doctor consultations, enhanced diagnostics, and personalized care.
AI chatbots are at the cornerstone of these tendencies. Natural language processing (NLP) allows smooth patient communication, bringing patients a customized experience. Chatbot systems can gather patient data, assess symptoms, and deliver guidance. This way, patients can gain healthcare insights almost instantly and win some time before an offline consultation with a physician.
AI is expected to make healthcare services more accessible to patients. It will also keep expanding the reach of telemedicine, closing the gap between patients and physicians even if they are spread across the globe.
Remote patient monitoring
The future of remote patient monitoring will largely depend on AI. The numbers speak for themselves: AI-powered systems have been proven to reduce patient readmission by almost 50%, according to Medical Economics. Let’s review some insights behind the striking statistics.
First, AI enables the processing of large amounts of data, allowing for more precise identification of symptom patterns and prediction of health risks. For example, AI algorithms can be trained to determine irregular heart rhythms, enabling early doctor intervention.
Moreover, AI-powered remote patient monitoring reduces the strain on doctors and other medical staff. Instead of continuous patient management, physicians and nurses are notified whenever they need to be engaged. This way, medical staff attention isn’t scattered, and they direct maximum effort to situations that require sharp focus.
As AI makes remote patient monitoring even more precise, predictive, and personalized, hospitals and physicians will continue adopting this technology in 2025. According to Statista, the remote patient monitoring market will grow from $93bn in 2025 to $134bn by 2029, paving the way for AI-driven remote patient monitoring solutions.
Image analysis in skin health
In 2025, visiting a doctor each time you need to detect or track the course of skin diseases is becoming unnecessary. Computer vision-powered apps can replace frequent dermatologist visits, which is especially critical for people with decreased mobility. However, even more important is that AI solutions enable early detection of skin diseases, improving patients’ recovery prospects.
Computer vision apps for skin disease tracking and monitoring detect skin issues using a pre-trained ML model. Such apps track the skin’s state and collect historical data on disease progress using computer vision. From the users’ side, it works as simple as this: a patient opens an app, turns on the camera, and points it at the skin area. After the system analyzes the skin, it provides a report on the current state of the skin disease.
At this point, some computer vision apps for skin disease monitoring have already been approved as reliable diagnostic tools by governmental authorities like the FDA. For one, a DermaSensor device is proven to decrease the number of missed skin cancers. Such devices provide a scrupulous analysis of cellular and subcellular skin layers, enabling unprecedented diagnostic accuracy.
The trend for using AI-powered apps and devices for skin disease detection, monitoring, and treatment is expected to grow in 2025. Whether struggling with a chronic skin disease or a sudden life-threatening skin condition, AI-powered apps promise patients an improved diagnostic rate and increased recovery chances.
Hospital management software
AI-powered hospital management systems have already reduced 40% of administrative tasks and improved medical staff allocation by 25%, according to thoughtful.ai. Medical facilities worldwide are witnessing healthcare staff shortages, which are decreasing the quality of patient care and treatment. That’s why innovative solutions such as AI-driven hospital management software will remain in high demand throughout 2025.
Besides improving hospital operations efficiency, AI boosts the accuracy of clinical decisions. Analyzing vast amounts of patient data and utilizing predictive analytics enables timely intervention whenever the patient needs immediate attention.
Moreover, AI-driven hospital solutions are expected to improve hospitals' financial performance globally. According to Accenture, AI HMSs can save up to $150 billion in annual expenses, making them a win-win investment for hospitals.
Drug development
Some big pharma corporations utilize AI to streamline drug development and clinical trials. One prominent example is Pfizer, which used AI to develop its oral COVID-19 treatment, PAXLOVID™. Another case is AstraZeneca, which will use an AI model to run cancer trials, costing the company $18 million.
The ability to analyze extensive amounts of data makes AI a prominent technology for drug discovery. For example, AI can predict molecular structures by screening billions of molecules. This allows pharmaceutical companies to identify viable drug candidates early in the discovery phase.
Even more prominent is the opportunity to minimize human and animal testing with the help of AI. Predictive models can replace traditional assessments, enhancing the accuracy of defining potential side effects of the drug under development.
All in all, AI paves the way for more ethical and efficient drug development. This means we’ll witness increased use of AI in the pharmaceutical industry, even more AI-driven clinical trials, and the development of specific government regulations overseeing the use of AI in drug development. These may vary from country to country. For one, European governments have already devised an EU AI Act in healthcare to regulate the proper use of AI for healthcare products and services.
Summing up
In 2025, AI will already be deeply rooted in healthcare software development processes. Though AI's applications in healthcare have limitless potential, in this article, we’ve covered the most trendy and relevant areas of healthcare that are expected to benefit from AI the most in 2025.
First and foremost, AI will continue to make remote patient monitoring more convenient for physicians and patients. Skin diseases, whether chronic or unexpected short-term issues, will become easier to detect and treat, increasing patients’ recovery prospects.
Another area that AI can improve is hospital management. AI-driven systems will continue to improve medical staff allocation and make treatment more efficient. Last but not least is drug development. AI clears the way for more ethical and efficient drug discovery and development.
