Artificial Intelligence has an excellent ability to analyze medical images such as X-rays, CT scans, and MRIs to detect abnormalities. Artificial Intelligence algorithms learn from large amounts of image data and can identify microscopic lesions and abnormalities with high accuracy. This increases the likelihood of detecting lesions earlier than with traditional diagnostic methods, allowing for early treatment.
Artificial Intelligence can also predict the risk of disease by incorporating data such as medical history, symptoms, and test results. Predictive diagnosis through Artificial Intelligence can help in taking appropriate tests and preventive measures before symptoms develop, contributing to the early detection and prevention of diseases. This allows for early detection of diseases that may develop in the future based on the symptoms a patient experiences, improving the quality of healthcare.
Artificial Intelligence will analyze a patient's medical history, current condition, and the effectiveness of treatments to suggest the optimal treatment plan, which will allow the selection of the most suitable treatment for each patient and improve the treatment success rate.
Artificial Intelligence can accumulate huge amounts of patient data, extract genetic information, lifestyle habits, medical history, etc., and provide personalized treatment, thereby improving the effectiveness of treatment and reducing the risk of side effects.
Artificial Intelligence can predict the risk of developing a disease. For example, by using models that predict the risk of heart disease or diabetes, preventive measures can be taken early, preventing the onset of diseases and improving the quality of healthcare.
Artificial Intelligence can also be used to suggest lifestyle improvements and preventive measures based on individual patient health data. For example, it can suggest ways to improve lack of exercise and diet, helping to reduce the risk of developing diseases. Also, by monitoring health status in real time, abnormalities can be identified early and appropriate measures can be taken. This will promote the implementation of preventive medicine and support health maintenance.
Risk of oversight and misdiagnosis While Artificial Intelligence offers many benefits to healthcare providers, it also carries the risk of misdiagnosis or oversight, especially when rare diseases or new outbreaks are difficult to treat or when healthcare professionals are unable to correctly interpret the results presented by Artificial Intelligence.
Even in image diagnosis using Artificial Intelligence (AI), there is a risk that AI may incorrectly identify normal images as abnormal or, conversely, judge abnormal images as normal. When introducing AI, it is essential to be aware of these risks in their entirety and to carry out appropriate verification and monitoring.
In the unlikely event that a misdiagnosis occurs due to AI, the question of who is responsible becomes important. In general, AI is seen as a tool that assists in diagnosis, with the final diagnosis being made by healthcare professionals. Therefore, if a misdiagnosis occurs due to AI, the responsibility lies with healthcare professionals and medical institutions. However, if there is a problem with the AI algorithm or data, liability can also extend to the developer or provider.
With the introduction of AI, the handling of patient data becomes a major issue. Patients’ personal information and medical data are subject to privacy protection. Because AI systems analyze this data, medical institutions must protect the data and take ethical measures. They must obtain patient consent, anonymize the data, and take security measures. Measures are required to prevent data leaks and unauthorized use.
In addition, AI systems may be at risk of cyberattacks and data breach. To prevent this, it is important to take security measures for AI systems. By taking appropriate security measures, you can protect patient data and ensure the reliability of the system.
Educating healthcare professionals on how to use AI tools To effectively leverage AI, healthcare professionals must understand AI technology and have the skills to use it appropriately. Healthcare professionals must be able to evaluate the results produced by AI and reflect them in treatment plans. This requires training to understand the basic mechanisms and limitations of AI. Healthcare professionals need to acquire the skills needed to work with AI to provide optimal medical care to patients.
For AI and healthcare professionals to collaborate effectively, a clear division of roles and communication between staff is essential. AI will assist in diagnosis and treatment, but the final decision will be made by healthcare professionals. Based on AI suggestions, healthcare professionals will make decisions to provide the best medical care to patients. To enhance collaboration between AI and healthcare professionals, training and support are needed to correctly interpret AI results and take appropriate action.