Functional Recovery Trajectory Prediction and Adaptive Therapy Scheduling: Machine Learning Approaches to Enhanced Patient Outcomes in Rehabilitation Medicine

Authors

  • Jérémy Fix Associate Professor of Human-Computer Interaction, University of Toulouse

Keywords:

functional recovery trajectory prediction, adaptive therapy scheduling, machine learning approaches to enhanced patient outcomes, rehabilitation medicine

Abstract

Improving patient outcomes is a critical aim for any healthcare system. New technological capabilities, particularly in machine learning and artificial intelligence, have led to proof of concepts that can be leveraged in healthcare. Whether for improving workflows, out-of-clinic interventions, or enhancing treatments or pharmaceutical regimens, these emerging methods have vast potential in enhancing population health.

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Published

31-12-2025

How to Cite

[1]
“Functional Recovery Trajectory Prediction and Adaptive Therapy Scheduling: Machine Learning Approaches to Enhanced Patient Outcomes in Rehabilitation Medicine”, J. of Art. Int. & Research, vol. 5, no. 2, pp. 11–21, Dec. 2025, Accessed: Jun. 05, 2026. [Online]. Available: https://thesciencebrigade.com/JAIR/article/view/824