Work

Denoising Autoencoders for the Detection of Patients Out of Distribution of Healthy Individuals

Year: 2024

Type: conference-paper

Abstract: This paper uses a Denoising AutoEncoder (DAE) to detect patients who are out of the distribution of healthy individuals.A DAE is trained only on healthy individuals.In the testing phase, the trained DAE is used to reconstruct healthy and pathological individuals with masked features.An error of reconstruction is computed on the masked features of the two families and compared.This paper shows the difference between the distributions of the error of reconstruction.This difference leads to the use of this method for classification.

Source: Computing in cardiology

DOI: 10.22489/cinc.2024.268

Authors: MARIETTE DUPUY, Remi Dubois, Marie Chavent

Institutions: Université de Bordeaux, Centre Inria de l'université de Bordeaux, Centre de Recherche Cardio-Thoracique de Bordeaux, ASTRAL: Méthodes avancées d'apprentissage statistique et de contrôle

Language: English

Topic: Anomaly Detection Techniques and Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: bronze

Funder: Agence Nationale de la Recherche