AI-based differential diagnosis of dementia etiologies on multimodal data.

C, Xue; SS, Kowshik; D, Lteif; S, Puducheri; VH, Jasodanand; OT, Zhou; AS, Walia; OB, Guney; JD, Zhang; S, Poésy; A, Kaliaev; VC, Andreu-Arasa; BC, Dwyer; CW, Farris; H, Hao; S, Kedar; AZ, Mian; DL, Murman; SA, O'Shea; AB, Paul; S, Rohatgi; MH, Saint-Hilaire; EA, Sartor; BN, Setty; JE, Small; A, Swaminathan; O, Taraschenko; J, Yuan; Y, Zhou; S, Zhu; C, Karjadi; Ang TF, Alvin; SA, Bargal; BA, Plummer; KL, Poston; M, Ahangaran; R, Au; VB, Kolachalama

doi:10.1038/s41591-024-03118-z

Public

AI-based differential diagnosis of dementia etiologies on multimodal data.

Shared by NobleBlocks on Jul 4, 2024 • 12:00 AM UTC

Authors:

Xue C

Kowshik SS

Lteif D

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...

Research Assistant

AI chat, annotations, notes & similar papers

Finding related papers...

Discussions

(0)

No comments yet

Be the first to share your thoughts!