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The use of artificial intelligence, or AI, in the medical industry is expanding quickly, particularly in the areas of diagnosis and therapy administration. There has been extensive research on how AI can support clinical judgement and increase physician efficiency over time. Artificial intelligence can assist providers in a variety of patient care and intelligent health systems. In medical diagnostics, artificial intelligence facilitates medical management, automation, administration, and workflows.
Recent studies suggest that machine learning diagnostic applications can be divided into four groups:
1. Chatbots: Companies are utilising AI chatbots with speech recognition capabilities to find patterns in patient symptoms to make a possible diagnosis, prevent disease, and/or suggest a suitable course of action.
2. Oncology: Scientists are using machine learning to teach algorithms to identify malignant tissue at a level comparable to that of skilled physicians.
3. Pathology: The medical field of pathology focuses on disease diagnosis via laboratory examinations of tissues, including blood and urine, as well as bodily fluids. Machine learning techniques like machine vision can improve work that is typically only done by pathologists using microscopes.
4.Rare Diseases: To aid clinicians in the diagnosis of rare diseases, facial recognition technologies and machine learning are being integrated. Deep learning and face analysis are used to analyse patient photographs to find phenotypes that match rare genetic disorders.
1)German researchers from the University of Bonn have developed an AI-based method for improving leukaemia diagnosis from blood samples. They created a machine learning method based on testing bone marrow or blood for the presence of lymphatic system cancer.
2) In the UK, scientists at Queen Mary University of London have discovered a way to utilise AI to analyse blood from rheumatoid arthritis patients and determine how they will respond to treatment.

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