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Research Opportunities
Bioengineering, Computer and Computational Engineering, Electrical and Computer Engineering, Artificial Intelligence and Data Science, and related fields
Work description
The fellow will contribute to developing artificial intelligence-based solutions for the automated analysis of polysomnography (vPSG) videos in the context of diagnosing sleep disorders, particularly REM sleep behavior disorder (RBD). The activities to be performed will include:
Training and validation of machine learning models, ensuring the quality and consistency of the datasets used. Development and implementation of computer vision algorithms for detecting and analyzing RBD-specific behaviors in vPSG videos. Integration and testing solutions in a simulated clinical environment, ensuring the applicability of the developed models in clinical practice. Participate in the analysis of results and benchmark the system against manual expert evaluation, aiming to measure gains in accuracy and efficiency. Contribution to the scientific dissemination of the project, including writing scientific articles,
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