Artificial intelligence (AI) is rapidly entering routine clinical practice, moving beyond experimental settings into practical tools that support physicians in diagnosis, imaging interpretation, and clinical documentation. Machine learning algorithms can analyse large datasets from electronic health records (EHRs), laboratory results, and imaging studies, enabling faster identification of disease patterns and clinical risk factors. In radiology, dermatology, and ophthalmology, AI-based systems have demonstrated performance comparable to specialists in detecting conditions such as diabetic retinopathy, skin malignancies, and pulmonary nodules .
In diagnostic workflows, AI tools can assist clinicians by flagging abnormal findings, predicting disease risk, and suggesting differential diagnoses based on patient data. Similarly, natural language processing (NLP) technologies are…
