Spinal Muscular Atrophy Hypotonia Detection Using Computer Vision and Artificial Intelligence-Reference-Cited by-同舟云学术

Spinal Muscular Atrophy Hypotonia Detection Using Computer Vision and Artificial Intelligence

Published:2024-05-01 Issue:5 Volume:178 Page:500
ISSN:2168-6203
Container-title:JAMA Pediatrics
language:en
Short-container-title:JAMA Pediatr

Author:

Taleb Adel¹,Rambaud Philippe¹,Diop Samuel²,Fauches Raphaël¹,Tomasik Joanna³,Jouen François⁴,Bergounioux Jean⁵

Affiliation:

1. SogetiLabs, Issy-les-Moulineaux, France

2. OSO-AI, Brest, France

3. Laboratoire interdisciplinaire des sciences du numérique, Centrale Supélec, Université Paris-Saclay, Gif-sur-Yvette, France

4. Human and Artificial Cognitions Laboratory, Ecole Pratique des Hautes Etudes, PSL University, Paris, France

5. Simone Veil Health Medical School, Université Versailles Saint-Quentin-en-Yvelines, Paris-Saclay, France

Abstract

This case-control study uses computer vision and artificial intelligence to develop a screening tool for detecting spinal muscular atrophy in infants.

Publisher

American Medical Association (AMA)

Link

https://jamanetwork.com/journals/jamapediatrics/articlepdf/2815518/jamapediatrics_taleb_2024_ld_240002_1714765540.40386.pdf

Reference5 articles.

1. New treatments in spinal muscular atrophy.;Gowda;Arch Dis Child,2023

2. diagnosis and management of spinal muscular atrophy: Part 1: recommendations for diagnosis, rehabilitation, orthopedic and nutritional care.;Mercuri;Neuromuscul Disord,2018

3. Lundberg? S, Lee? S-I. A unified approach to interpreting model predictions.? arXiv. Preprint posted online November 24, 2017. doi:10.48550/arXiv.1705.07874

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