Article

DETECT: Feature extraction method for disease trajectory modeling

2022-11-13

Abstract excerpt

Modeling with longitudinal electronic health record (EHR) data proves challenging given the high dimensionality, redundancy, and noise captured in EHR. In order to improve precision medicine strategies and identify predictors of disease risk in advance, evaluating meaningful patient disease trajectories is essential. In this study, we develop the algorithm D iseas E T rajectory f E ature extra CT ion ( DETECT) for...

Topics

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

Identifiers and source

Literature Corpus work: 974b32b9-0a79-56d9-93f6-734f25daceb9
DOI: 10.1101/2022.11.06.22281817

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

DETECT: Feature extraction method for disease trajectory modelingDOI 10.1101/2022.11.06.22281817Read

Clustering of patient comorbidities within electronic medical records enables high-precision COVID-19 mortality predictionSemantic proximity Read

Clustering of patient comorbidities within electronic medical records enables high-precision COVID-19 mortality predictionSemantic proximity Read

Multimodal Electronic Health Record Foundation Models with Electrocardiogram for Cardiovascular Disease PredictionSemantic proximity Read

Exploratory electronic health record analysis with ehrapySemantic proximity Read

High-throughput Phenotyping with Temporal SequencesSemantic proximity Read

Detecting time-evolving phenotypic topics via tensor factorization on electronic health records: Cardiovascular disease case study.Semantic proximity Read

DEPOT: graph learning delineates the roles of cancers in the progression trajectories of chronic kidney disease using electronic medical recordsSemantic proximity Read

An explainable transformer model learning from entire treatment timelines for pan-cancer risk profiling across healthcare systemsSemantic proximity Read

Characterization of long COVID temporal sub-phenotypes by distributed representation learning from electronic health record data: a cohort studySemantic proximity Read

ALADYNOULLI: A Bayesian approach to disease progression modeling for genomic discovery and clinical predictionSemantic proximity Read

Longitudinal modeling of multimorbidity trajectories using large language modelsSemantic proximity Read

Predicting morbidity by Local Similarities in Multi-Scale Patient TrajectoriesSemantic proximity Read