[Pre-print] End-to-End Models for the Analysis of Pupil Size Variations and Diagnosis of Parkinson’s Disease

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A new pre-print is online. It summarizes a work carried out in collaboration with the University of Genova. It consists of an automatic analysis of pupil size sequences, recorded with an eye-tracker, using machine learning techniques. The study shows how it is possible to build models for the diagnosis of Parkinson’s disease learned automatically from the data.

The pre-print can be viewed and downloaded here: https://arxiv.org/abs/2002.02383

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