Learning meaningful latent space representations for patient risk stratification: Model development and validation for dengue and other acute febrile illness

Learning meaningful latent space representations for patient risk stratification: Model development and validation for dengue and other acute febrile illness

BackgroundIncreased data availability has prompted the creation of clinical decision support systems. These systems utilise clinical information to enhance health care provision, both to predict the likelihood of specific clinical outcomes or evaluate the risk of further complications. However, thei...

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Main Authors: Bernard Hernandez, Oliver Stiff, Damien K. Ming, Chanh Ho Quang, Vuong Nguyen Lam, Tuan Nguyen Minh, Chau Nguyen Van Vinh, Nguyet Nguyen Minh, Huy Nguyen Quang, Lam Phung Khanh, Tam Dong Thi Hoai, Trung Dinh The, Trieu Huynh Trung, Bridget Wills, Cameron P. Simmons, Alison H. Holmes, Sophie Yacoub, Pantelis Georgiou, on behalf of the Vietnam ICU Translational Applications Laboratory (VITAL) investigators
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-02-01
Series:Frontiers in Digital Health
Subjects:
autoencoder (AE) neural networks
unsupervised learning
similarity retrieval
visualisation
clinical decision support system (CDSS)
dengue
Online Access:https://www.frontiersin.org/articles/10.3389/fdgth.2023.1057467/full

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https://www.frontiersin.org/articles/10.3389/fdgth.2023.1057467/full

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