Learning and visualizing chronic latent representations using electronic health records
Abstract Background Nowadays, patients with chronic diseases such as diabetes and hypertension have reached alarming numbers worldwide. These diseases increase the risk of developing acute complications and involve a substantial economic burden and demand for health resources. The widespread adoptio...
Main Authors: | David Chushig-Muzo, Cristina Soguero-Ruiz, Pablo de Miguel Bohoyo, Inmaculada Mora-Jiménez |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2022-09-01
|
Series: | BioData Mining |
Subjects: | |
Online Access: | https://doi.org/10.1186/s13040-022-00303-z |
Similar Items
-
Data-Driven Visual Characterization of Patient Health-Status Using Electronic Health Records and Self-Organizing Maps
by: David Chushig-Muzo, et al.
Published: (2020-01-01) -
Visually guided classification trees for analyzing chronic patients
by: Cristina Soguero-Ruiz, et al.
Published: (2020-03-01) -
Investigation of the effectiveness of a classification method based on improved DAE feature extraction for hepatitis C prediction
by: Lin Zhang, et al.
Published: (2024-04-01) -
Dynamically Meaningful Latent Representations of Dynamical Systems
by: Imran Nasim, et al.
Published: (2024-02-01) -
Affective Latent Representation of Acoustic and Lexical Features for Emotion Recognition
by: Eesung Kim, et al.
Published: (2020-05-01)