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Research Opportunities

Bioengineering, Computer Engineering and Computing, Electrical and Computing, Artificial Intelligence and Data Science and related areas

Work description

The fellow to be hired will contribute to the development of artificial intelligence-based solutions for automated analysis of polysomnography (vPSG) videos in the context of the diagnosis of sleep disorders, in particular REM sleep behavior disorder (RBD).

The activities to be performed aim to:

Annotation and preparation of data for training and validation of machine learning models, ensuring the quality and coherence of the data sets used. Development and implementation of computer vision algorithms for detecting and analyzing specific RBD behaviors in vPSG videos. Integration and testing of solutions in a simulated clinical environment, ensuring the applicability of the models developed in medical practice. Participation in the analysis of results and in the benchmarking of the system against the manual evaluation of experts,

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