Marco Cascella, Maria Teresa Avella, Marcello Di Pumpo, E. Sebastiani, Martino Bussa, Alessio Tagliaferri, Barbara Brunetti, Pierluigi Meloni, Elisa Bianchini, Paolo Graziani, Federico Faustini, Guido D’Onofrio, David Manetta, Cristina Angela Catania, Cristina Imbesi, Cesare Pane, Roberta Fusco, Vincenza Granata
BACKGROUND: Artificial intelligence (AI) is rapidly transforming medicine through advanced diagnostic, prognostic, and decision-support systems. OBJECTIVE: To summarize the fundamental concepts, clinical applications, ethical issues, and future perspectives of AI in healthcare. METHODS: A narrative review of current evidence on machine learning, deep learning, neural networks, and AI applications across major medical specialties was conducted. RESULTS: AI demonstrated high performance in diagnostic support, prognostic prediction, medical imaging, and personalized medicine. However, limitations related to data quality, generalizability, transparency, and ethical concerns remain significant challenges. CONCLUSIONS: AI has strong potential to improve healthcare delivery and precision medicine, although robust validation, ethical oversight, and appropriate regulation are essential for safe clinical implementation.