SHAPING THE FUTURE OF MEDICINE: AI IN CLINICAL DECISION-MAKING

Abstract

Artificial intelligence (AI) is profoundly transforming medicine by enhancing clinical decision-making across specialties. Informed by recent reviews and studies, this narrative synthesizes how AI technologies – from machine learning (ML) and deep learning (DL) to large language models (LLMs) – are integrated into healthcare. We discuss AI’s roles in diagnosis, prognosis, personalized treatment, and workflow optimization. Highlighting applications in radiology, pathology, cardiology, oncology, ophthalmology, primary care, emergency medicine, and critical care, we illustrate the broad impact of AI tools. We also address challenges (data bias, interpretability, ethics, regulation) and describe emerging trends such as human–AI collaboration and patient-generated data. Evidence indicates that AI systems can improve diagnostic accuracy, expedite triage, and personalize interventions, although real-world validation and governance frameworks remain crucial. We conclude with a forward-looking outlook on integrating AI into routine care, promoting enhanced outcomes and efficiency.