Dear Colleagues,

The rapid advancement of Artificial Intelligence (AI) in healthcare is transforming the way medical data is analyzed, diagnoses are made, and treatments are personalized. This Topical Collection on AI in Medicine aims to bring together cutting-edge research, methodologies, and applications that leverage AI and Data Science to address key challenges in healthcare. Potential contributions include the development of intelligent diagnostic tools, predictive models for patient outcomes, personalized treatment recommendations, and the integration of heterogeneous medical datasets for improved clinical decision-making.

By focusing on AI in the medical domain, this collection encourages submissions that explore both theoretical innovations and practical implementations. Topics of interest include machine learning algorithms for medical imaging, natural language processing of electronic health records, predictive analytics in epidemiology, AI-driven drug discovery, and ethical considerations in deploying AI in clinical settings.

The goal of this collection is to provide a comprehensive overview of how AI and data-driven approaches can enhance patient care, optimize healthcare workflows, and foster innovation in medical research. We invite authors to submit original research, review articles, and case studies that demonstrate the potential and impact of AI technologies in medicine. This collection will serve as a guide for researchers, practitioners, and policy-makers interested in the intersection of AI, Data Science, and healthcare.

Dr. Otmane Azeroual
Dr. Robert Friedman
Collection Editors