Computer Vision and Deep Learning in Clinical Neuroscience: Methods, Applications and Future Directions

Dear Colleagues,

We invite submissions for this Special Issue of Applied Sciences, related to computer vision and deep learning in clinical contexts, with a particular focus on applications in neurology, psychiatry, geriatrics, and movement sciences. As large quantities of visual data from clinical examinations, video recordings, and imaging are often routinely available, artificial intelligence (AI)—particularly computer vision (CV) and deep learning (DL)—offers powerful tools for objective, scalable, and reproducible analysis. As such, these methods hold great potential in overcoming central challenges in modern medical practice. This Special Issue aims to showcase interdisciplinary work that bridges computer science, engineering, medical and neuroscience, and clinical practice. We welcome original research and reviews on CV/DL methods applied to the quantification of clinically meaningful outcomes, as well as diagnosis, prognosis, or treatment monitoring in neurological, psychiatric, and movement-related conditions. Topics of interest include, but are not limited to, video-based motion analysis, facial or eye movement tracking, gait and posture assessment, multimodal data fusion, neuroimaging analysis, explainable AI, and clinical validation frameworks. We particularly encourage contributions addressing real-world clinical integration, ethical considerations, and accessibility in low-resource settings, as well as in underrepresented groups. Both technical and translational studies are welcome.

Dr. Maximilian Friedrich
Prof. Dr. Jane E. Alty
Guest Editors

Manuscript Submission Information

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