Machine learning (ML) is transforming precision medicine by enhancing patient outcomes in diverse clinical settings. This study examines how ML models can address data challenges and reduce algorithmic bias-key issues in contemporary healthcare analytics. By utilizing extensive datasets encompassing patient demographics, genetic profiles, treatment responses, and clinical outcomes, the research demonstrates that well-implemented ML improves diagnostic precision and fosters equitable care by pinpointing outcome disparities across different groups. Notable progress in predicting personalized treatment options emphasizes the importance of robust data governance to guarantee ethical deployment of these technologies. This work underlines MLs potential to strengthen clinical decision-making, deliver individualized healthcare solutions, and ultimately advance the field of precision medicine. Through responsible integration into clinical practices, ML can reshape healthcare delivery, enhance patient engagement, and mitigate disparities, affirming its growing significance in the evolution of medicine.
Transformative Role of Machine Learning in Precision Medicine for Enhanced Healthcare Environments
Arena, Fabio;Collotta, Mario;Pau, Giovanni;Ricciardello, Angela;Ruggieri, Marianna;Salerno, Valerio Mario;Scuro, Carmelo
2025-01-01
Abstract
Machine learning (ML) is transforming precision medicine by enhancing patient outcomes in diverse clinical settings. This study examines how ML models can address data challenges and reduce algorithmic bias-key issues in contemporary healthcare analytics. By utilizing extensive datasets encompassing patient demographics, genetic profiles, treatment responses, and clinical outcomes, the research demonstrates that well-implemented ML improves diagnostic precision and fosters equitable care by pinpointing outcome disparities across different groups. Notable progress in predicting personalized treatment options emphasizes the importance of robust data governance to guarantee ethical deployment of these technologies. This work underlines MLs potential to strengthen clinical decision-making, deliver individualized healthcare solutions, and ultimately advance the field of precision medicine. Through responsible integration into clinical practices, ML can reshape healthcare delivery, enhance patient engagement, and mitigate disparities, affirming its growing significance in the evolution of medicine.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
