Today's advances in AI and machine learning are fuelling a digital revolution in pathology and radiology, enabling researchers to go far beyond what was possible just five to ten years ago.
One of the key aspects of diagnostics is being able to identify anomalies, and advanced analysis of images using machine learning and AI algorithms are increasingly helping to detect patterns that can make that process faster and far more accurate.
AI algorithms are being used to more effectively analyse CT scans, MRIs, and X-rays for abnormalities such as fractures, haemorrhages, and tumours, assisting medical staff in more quickly identifying what treatment is required, as well as assisting emergency medical staff in triaging serious cases.
AI can also assist researchers in detecting and grading cancer from histopathological images, critically enabling them to catch cancer and other diseases at much earlier stages and allowing for earlier and more effective intervention.
Recent advances in computational pathology and omics technologies have made it possible to generate complex, personalised health data on a large scale, improving the prediction of treatment outcomes.
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