CFP

SMLHS2025: Statistical Machine Learning in Medicine, Sports, and Health Systems: A Practical Guide

Submission link	https://easychair.org/conferences/?conf=smlhs2025
Poster	(download)
Submission deadline	November 30, 2026

Topics: machine learning quantitative analysis in medicine medical statistics occupational health data analytics

Statistical Machine Learning in Medicine, Sports, and Health Systems: A Practical Guide is envisioned as a comprehensive and practical resource that combines theoretical foundations with methodological developments and real-world applications. The book aims to provide valuable insights for researchers and practitioners seeking to harness statistics and machine learning across medicine, sports science, and health systems. The volume will emphasize rigorous methodologies, real-world applications, practical case studies, and actionable strategies for addressing data-driven challenges in these rapidly evolving domains.

Submission Guidelines

This book invites contributions from researchers and practitioners working at the intersection of statistics, machine learning, medicine, sports science, and health systems. Chapters should be self-contained and fall into one of the following categories:

Original Works: Presenting original research within the scope of the book.
Experiments: Addressing applied analytics scenarios and real-world problems.
Review / Survey: Providing comprehensive reviews of recent developments and emerging areas of interest.
Expanded Works: Extended versions of previously published work in relevant outlets are also encouraged, provided that they contain a minimum of 50% new content, clearly identified as such.

List of Topics

Contributions are welcome on subjects related to, but not limited to, the following areas:

Medicine

Machine Learning in Healthcare
Quantitative Analysis in Medicine
Medical Data Analytics
Personalized Medicine Using Machine Learning
Health Informatics and Predictive Analytics
Mental Health Analytics

Sports

Quantitative Analysis in Sports
Sports Medicine Data Analytics
Predictive Modeling for Sports Performance
Injury Prediction and Prevention
Data-Driven Training and Coaching Strategies
Machine Learning in Sports Rehabilitation
Predictive Analytics for Injury Recovery
Wearable Technology and Health Analytics
Player Performance Analytics
Health Monitoring via IoT Devices in Sports

Health Systems

Occupational Health and Safety Data Analytics
Health Economics and Cost-Effectiveness Modeling
Healthcare Supply Chain and Logistics Analytics
Pharmaceutical Cold Chain and Distribution Analytics
Global Health Logistics and Trade
Resource Allocation and Capacity Planning
Health Policy Analytics
Hospital Operations and Workflow Optimization
Epidemiological Forecasting and Public Health Analytics

Editorial Team

- Foued SAADAOUI, Professor of Statistics, PhD, International University of Rabat, Morocco. foued.saadaoui@uir.ac.ma
- Hana RABBOUCH, Associate Professor of Computer Sciences, PhD, Department of Business Computing, Higher Institute of Management of Sousse, Tunisia. hana.rabbouch@isg-sousse.tn
- Frédéric DUTHEIL, Professor of Medicine, MD, PhD, Head of Occupational Medicine, University Hospital of Clermont-Ferrand, France. fred_dutheil@yahoo.fr

Publication

The book will be published by CRC Press, Taylor & Francis Group, with publication anticipated in late 2027.

Contact

All questions about submissions should be emailed to hana.rabbouch@isg-sousse.tn