About

The Journal of Machine Learning for Healthcare Decision Support (JMLHDS) is a peer-reviewed publication dedicated to advancing the theory, algorithms, and applications of machine learning (ML) techniques for healthcare decision support. With the increasing complexity of healthcare data and the growing demand for evidence-based decision-making, JMLHDS provides a platform for researchers, clinicians, and industry professionals to explore innovative ML solutions that improve clinical outcomes, enhance patient safety, and optimize healthcare delivery. The journal covers a wide range of topics, including predictive modeling, risk stratification, treatment optimization, clinical pathway analysis, and healthcare analytics. JMLHDS welcomes original research articles, review papers, and case studies that demonstrate the effectiveness and impact of ML technologies in healthcare decision support. By fostering collaboration between ML researchers and healthcare practitioners, JMLHDS aims to accelerate the translation of ML innovations into clinical practice and promote data-driven approaches to healthcare decision-making.