Article

Deep Representation Learning for Risk Prediction in Electronic Health Records Using Self-Supervised Methods

2026-02-05

Abstract excerpt

This study proposes a self-supervised representation learning-based risk prediction model to address the challenges of label scarcity, structural complexity, and high heterogeneity in Electronic Health Records (EHR) data for risk assessment tasks. The model combines masked reconstruction and context prediction to automatically learn temporal dependencies and latent semantic structures in EHR data under unlabeled c...

Topics

Open a Topic to create a Post that cites this publication.

Sepsis Diagnosis and Treatment

Identifiers and source

Literature Corpus work: da8da5b1-02ba-533a-b680-9b753f1756b9
DOI: 10.20944/preprints202602.0360.v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Deep Representation Learning for Risk Prediction in Electronic Health Records Using Self-Supervised MethodsDOI 10.20944/preprints202602.0360.v1Read

EHR Foundation Models Improve Robustness in the Presence of Temporal Distribution ShiftSemantic proximity Read

Longitudinal Masked Representation Learning for Pulmonary Nodule Diagnosis from Language Embedded EHRsSemantic proximity Read

Enformer: An encoder-decoder generative model to enhance prediction of disease outcomes using electronic health recordsSemantic proximity Read

Disease Risk Prediction Using Structured EHR Data: Can Generalist Large Language Models Match Specialized Clinical Foundation Models? A Comparative Evaluation with Fine-TuningSemantic proximity Read

DeepMPM: a mortality risk prediction model using longitudinal EHR dataSemantic proximity Read

Combining structured and unstructured data for predictive models: a deep learning approachSemantic proximity Read

A Self-Explainable Dynamic Risk Monitoring Framework for Predicting Alzheimer’s Disease and Related DementiasSemantic proximity Read

EvolveFNN: An interpretable framework for early detection using longitudinal electronic health record dataSemantic proximity Read

Time-Aware Contrastive Transformer for Longitudinal Patient Representation LearningSemantic proximity Read

A Comparison of Representation Learning Methods for Medical Concepts in MIMIC-IVSemantic proximity Read

Developing Deep Learning Continuous Risk Models for Early Adverse Event Prediction in Electronic Health Records: an AKI Case StudySemantic proximity Read

InfEHR: Resolving Clinical Uncertainty through Deep Geometric Learning on Electronic Health RecordsSemantic proximity Read