Enhancing Clinical Psychology Practice through Data-Driven Machine Learning Monitoring Systems
Published in Cited Here, 2025
This research explores the intersection of machine learning and clinical psychology, developing data-driven monitoring systems that can enhance therapeutic practice. The work leverages multimodal data analysis — including behavioral signals, language patterns, and physiological markers — to provide clinicians with objective, quantitative insights into patient progress and treatment outcomes.
This interdisciplinary project connects my research in human behavior analysis and computer vision with real-world clinical applications, demonstrating how AI can augment (not replace) mental health professionals in providing better patient care.
Recommended citation: G. Martínez, A. Trujillo, J. Núñez, J.C.S. Jacques, A. Clapés, et al. (2025). "Enhancing clinical psychology practice through data-driven machine learning monitoring systems."
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