With the current rapid growth of AI, it has become widely used across different industries to enhance the decision-making processes and improve the overall quality of services. It is thus natural that artificial intelligence has also found its niche in digital diagnostics.
AI algorithms and machine learning have become critical tools in the process of analyzing data and assessing patients to find the diseases and conditions that they suffer from. Therefore, in this article, we explore the role of artificial intelligence in digital diagnostics and how it is used for the benefit of patients.
AI is capable of making diagnoses based on patterns in medical images that humans are unable to spot.
It enables making diagnoses earlier on.
AI is the cure to the problem of understaffed hospitals and clinics.
Human physicians, nurses, and PAs are still required for artificial intelligence to work properly and effectively.
The Role of AI in Digital Diagnostics
Artificial intelligence plays a crucial role in digital diagnostics. AI-powered rapid diagnostic tests, and machine learning for automating rapid diagnostic test interpretation – these are just two of the examples of how AI and the related technologies empower the diagnostic process. But, why is its role so critical?Artificial intelligence is capable of processing vast amounts of data, which often could be incomprehensible for a human or take too much time to analyze. As a result, AI-based algorithms may quickly evaluate the information provided about the patient – test results and medical history. They are capable of looking into them and finding elements that do not match – abnormal results that may indicate particular conditions, thus helping select the right direction for further tests or even make a proper diagnosis.
AI is also unaffected by human error. Based purely on algorithms, its performance does not depend on the time of the day, its energy or motivation levels, nor the mood. It is always objective and equally effective, which makes it ultimately dependable.
The Use of AI Algorithms and Machine Learning for Analyzing Medical Data and Assisting in the Diagnosis of Diseases and Conditions
AI and machine learning may be used to a far wider extent than just to quickly scan the test results and come up with proper diagnoses. It takes into account aspects that humans would rarely consider. How exactly is it utilized and what is it really capable of?
• Identifying patterns – AI is able to find patterns in medical imaging invisible to the human eye. This enables it to make diagnoses earlier on than any physician. As a result, the patients can be treated at the very beginning of their condition’s development and thus suffer less, avoid many symptoms, and get back to health much faster.
An example of that could be seen during the COVID-19 pandemic when AI was used to analyze lung images. It enabled more accurate identification of COVID-19-positive patients, thus leading to better treatment for both those suffering from this virus and those who had similar symptoms but a different condition.
• Predictions – Another way through which artificial-intelligence-driven digital diagnostics may be used to diagnose diseases as early as possible is through predictive analytics. AI may be used to analyze a patient’s medical history, with genetics taken into account as well, and then to predict the risks of particular conditions for that patient. This way, it provides the healthcare staff with a direction that they need to pursue, giving physicians and nurses answers to what tests should be further conducted.
• Remote diagnostics – The COVID-19 pandemic underlined the need and desire for contactless healthcare, something that was barely imaginable beforehand. Remote diagnostics have since become an integral part of healthcare, yet online consultations may still be limited just to the most common conditions. With artificial intelligence and machine learning, it is possible to finally move further in this aspect. Intelligent wristbands or monitors could be used to check the most important parameters of a patient, and thus make a much more accurate decision regardless of the distance.
• Alleviating staff shortage – With the high digital diagnostic capabilities of artificial intelligence, it is possible to battle one of the most prominent problems haunting healthcare – staff shortages. AI cannot be used on its own, it still requires human input, but it effectively reduces the time that the staff spends on every case. By introducing it widely into diagnostics, each physician would be able to diagnose more patients per day, thus enhancing the efficiency of the whole healthcare system.
Will AI Ever Be Capable of Diagnosing Diseases and Conditions on its Own?
Considering the wide usage of AI for digital diagnostics, it is not surprising that it poses a question: will AI replace physicians? While it is effective, sometimes better than humans, this will probably not happen in the near future. For artificial intelligence to work properly it has to operate within a set framework of rules and functions, and everything outside of it will still remain in the role of physicians, PAs, and nurses.