AI-based differential diagnosis of dementia etiologies on multimodal data

Xue, Chonghua; S Kowshik, Sahana; Lteif, Diala; Puducheri, Shreyas; Jasodanand, Varuna; Zhou, O.; S. Walia, Anika; Berke Güney, Osman; Diana Zhang, J.; Poésy, Serena; Kaliaev, Artem; Carlota Andreu‐Arasa, V.; Dwyer, Brigid; W. Farris, Chad; Hao, Honglin; Kedar, Sachin; Mian, Asim; L. Murman, Daniel; A. O’Shea, Sarah; B. Paul, Aaron; Rohatgi, Saurabh; Saint‐Hilaire, Marie; Alton Sartor, E.; N. Setty, Bindu; E. Small, Juan; Swaminathan, Arun; Taraschenko, Olga; Yuan, Jing; Zhou, Yan; Zhu, Shuhan; Karjadi, Cody; Fang Alvin Ang, Ting; Adel Bargal, Sarah; A. Plummer, Bryan; L. Poston, Kathleen; Ahangaran, Meysam; Au, Rhoda; B. Kolachalama, Vijaya

doi:10.1038/s41591-024-03118-z

Public

AI-based differential diagnosis of dementia etiologies on multimodal data

Published in Nature Medicine • Jul 4, 2024

Authors:

Chonghua Xue

Sahana S Kowshik

Diala Lteif

Abstract

Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an artificial intelligence (AI) model that harnesses a broad array of data, including demographi...

Subject

Dementia

Etiology

Differential diagnosis

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