Artificial intelligence in diagnostics and medical decision making

Artificial intelligence (AI) applications bear a great promise for healthcare. If successfully implemented, AI could reduce the workload for healthcare professionals and enhance the quality of work produced by reducing error and increasing precision. It could also extend medical knowledge and ameliorate clinical management. In addition, it has the potential to empower patients to participate more in medical decision making and taking more responsibility in their health management. However, robust and tangibly helpful decision support for medical advice is still in its infancy. Examples where AI can really have added value in guiding physicians in their expert opinion is currently scarce. Similarly, real progress based on big data analysis is also limited so far, for a large part due to qualitatively insufficient data input. However, in the area of medical diagnostics, such as imaging studies, interpretation of lab results or histopathology, major applications based on AI have already been introduced and sometimes implemented and act as serious associate to specialist professionals or can markedly reduce their workload. Currently the challenges associated with AI in healthcare are still significant. Accuracy of AI and will require more study and understanding of the capabilities and limitations of AI. Although AI may have advantages of speed and accuracy, at the moment physicians are still required for the more cognitively complex (or emotional) aspects and tasks.