AI algorithms can diagnose patients the way doctors do. For that, AI feeds on the data about previous diagnoses and learns to make its own diagnostic decisions. Then, the algorithms take in symptoms data and, if any, the data from wearables or medical images and analyze it against previous research mistakes, available treatment options, side effects, and diseases with similar symptoms to give a preliminary diagnosis.
Because AI can simultaneously process so much data, it has the potential to outperform humans in diagnosing diseases, from cancers to eye conditions. Moorfields Eye Hospital in London, for instance, uses AI-powered software to diagnose ocular conditions. AI diagnoses and offers treatment for over 50 diseases with 94% accuracy, which matches the performance of top medical experts.
We at ITRex have developed an AI-powered platform
that runs accurate power calculations for lenses implanted in patients as part of a treatment for cataracts, myopia, and other eye conditions.
Another example of AI in healthcare diagnosis is an AI platform
designed to collect, manage, and present data for patients diagnosed with cancer. The platform features a predictive analytics and decision support system that generates survival curves for newly-diagnosed patients based on the analysis of multiple patient-specific factors such as patient age, gender, comorbidity, cancer site, cancer stage, and tumor grade.
Applications of AI for diagnosis and treatment help: