AI and its Applications in Medicine (Part 1)
In the past few years, I have been writing about or engaging with topics related to various applications. It is an area that constantly sees new and fascinating examples every few months. Among the numerous fields where different use cases are rapidly developing and attempting to keep up with the latest technological advancements, I have had the opportunity to delve into the areas of education, fintech, law and artificial intelligence, tourism, and certain aspects of healthcare. In this column or perhaps in the next few columns, I will explore a highly interesting field: the application of AI in medicine. This is a strategically important area, considered by many to be one of the main domains with immense potential. I am pleased to notice that there are similar initiatives in Croatia, and this column serves as an announcement for all related events. One of the first conferences to be held is the AI & Robotics in Medicine Conference, co-organized by one of the renowned physicians in our country. Furthermore, it is even more positive that there exists an overarching organization called the Croatian Society for AI & Robotics in Medicine. We can hope that experts in other fields will organize themselves as well.
Of course, there are many well-known (and unknown) benefits and risks associated with the application of AI technology. However, let’s start with a few ideas on how artificial intelligence can assist in healthcare and make a positive contribution. Rapid and accurate diagnosis is crucial in treating diseases, and artificial intelligence (AI) helps physicians and other medical professionals obtain real-time precise data to optimize critical clinical decisions. The application of AI enables faster and more accurate results, which can lead to improvements in preventive measures, cost reduction, and decreased patient waiting times.
UI (User Interface) assists in improving the relationship between doctors and patients. Mobile devices can provide patients with essential health information, and mobile alerts can notify doctors and nurses of urgent changes in patient conditions and emergency cases. As one expert put it, “As AI technology continues to advance, more data can be collected than traditional medical institutions could ever gather.”
A part of the progress is also related to logistics. The application of AI allows for more efficient completion of complex tasks, such as scheduling organization, patient history tracking, identification of visual markers, and many others. AI applications also help minimize costs associated with insurance rejections and enable more precise and faster billing and payment processes.
A significant portion of these unnecessary costs is attributed to administrative efforts, such as filing claims, reviewing and resolving invoices. It is estimated that the healthcare industry loses approximately 200 billion dollars annually, according to some sources. Another area for improvement is determining medical necessity. Traditionally, it takes hours of reviewing patient history and information to accurately assess medical necessity. New natural language processing and deep learning algorithms can assist physicians in reviewing hospital cases and avoiding rejections.
Progress in this field frees up time and resources for medical professionals, allowing them to spend more time with patients and diagnose diseases. AI enables the collection of large amounts of data used in disease research.
A significant contribution is expected in assisting with new research. AI allows researchers to gather vast amounts of data from various sources. The ability to draw from a rich and growing body of information enables more efficient analysis of deadly diseases. With real-time data, research can benefit from a wide range of available information, provided it is easily translatable.
AI is also used for early symptom assessment and detection in disease progression. A very recent startup showcased its research data, promising exceptionally fast and early cancer diagnosis from certain blood sample tests (we are all, of course, cautious as memories of the Theranos startup are still fresh). Telehealth solutions are being implemented to monitor patient progress, recover vital diagnosis data, and contribute to population-wide information through shared networks. The contribution that can be created through social media and the communities formed there, in my opinion, is by no means negligible.
Considering that the medical profession is heavily burdened by the stress caused by the job itself (it is estimated that over 50% of physicians experience work-related stress), the application of AI can also be used to reduce stress among doctors who often face time pressures and other job demands. AI streamlines procedures and accelerates processes, lightening the burden on medical professionals.
This is a relatively extensive overview of some areas, each of which could be further explored and supported with detailed examples. Perhaps that could be the subject of a future column.
