Scanning the medical phenome to identify new diagnoses after recovery from COVID-19 in a US cohort
VE Kerchberger, JF Peterson… - Journal of the American …, 2023 - academic.oup.com
Objective COVID-19 survivors are at risk for long-term health effects, but assessing the
sequelae of COVID-19 at large scales is challenging. High-throughput methods to efficiently …
sequelae of COVID-19 at large scales is challenging. High-throughput methods to efficiently …
Knowledge-guided deep temporal clustering for Alzheimer's disease subtypes in completed clinical trials
Alzheimer's disease (AD) is a multifaceted neurodegenerative disorder with varied patient
progression. We aim to test the hypothesis that AD patients can be categorized into …
progression. We aim to test the hypothesis that AD patients can be categorized into …
Assessing Risk Factors for Cognitive Decline Using Electronic Health Record Data: A Scoping Review
L Wang, R Yang, Z Sha, AM Kuraszkiewicz… - Research …, 2024 - pmc.ncbi.nlm.nih.gov
Background: The data and information contained within electronic health records (EHR)
provide a rich, diverse, longitudinal view of real-world patient histories, offering valuable …
provide a rich, diverse, longitudinal view of real-world patient histories, offering valuable …
[HTML][HTML] Disease evolution and risk-based disease trajectories in congestive heart failure patients
Abstract Congestive Heart Failure (CHF) is among the most prevalent chronic diseases
worldwide, and is commonly associated with comorbidities and complex health conditions …
worldwide, and is commonly associated with comorbidities and complex health conditions …
A Self-Supervised Graph Neural Network to Identify Temporal Phenotypes of End-Stage Renal Disease Using Longitudinal Electronic Health Records
S Chi, Y Tian, X Li, F Wang, Y Wang, T Zhou… - Journal of Healthcare …, 2025 - Springer
End-stage renal disease (ESRD) represents high prevalence and substantial heterogeneity,
and individual variations within ESRD patients are poorly understood. We aim to employ …
and individual variations within ESRD patients are poorly understood. We aim to employ …
Age-associated proteins explain the role of medial temporal lobe networks in Alzheimer's disease
The structural connectivity (SC) of the medial temporal lobe and its associated cortical
anterior temporal and posterior medial networks (MTL-AT-PM) is linked to pathologies and …
anterior temporal and posterior medial networks (MTL-AT-PM) is linked to pathologies and …
Autoencoder to Identify Sex-Specific Sub-phenotypes in Alzheimer's Disease Progression Using Longitudinal Electronic Health Records
Alzheimer's Disease (AD) is a complex neurodegenerative disorder significantly influenced
by sex differences, with approximately two-thirds of AD patients being women …
by sex differences, with approximately two-thirds of AD patients being women …
Compensating trajectory bias for unsupervised patient stratification using adversarial recurrent neural networks
A Javer, O Parsons, O Carr, J Baxter, C Diedrich… - arXiv preprint arXiv …, 2021 - arxiv.org
Electronic healthcare records are an important source of information which can be used in
patient stratification to discover novel disease phenotypes. However, they can be …
patient stratification to discover novel disease phenotypes. However, they can be …
Temporal-informed phenotyping scans the medical phenome to identify new diagnoses after recovery from COVID-19
VE Kerchberger - 2022 - search.proquest.com
COVID-19 survivors are at risk for long-term health effects, but assessing the sequelae of
COVID-19 at large scales is challenging. High-throughput methods to efficiently identify new …
COVID-19 at large scales is challenging. High-throughput methods to efficiently identify new …