Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

High Throughput Phenotyping for Dimensional Psychopathology in Electronic Health Records.

Biological psychiatry - 15 Jun 2018

McCoy Thomas H, Yu Sheng, Hart Kamber L, Castro Victor M, Brown Hannah E, Rosenquist James N, Doyle Alysa E, Vuijk Pieter J, Cai Tianxi, Perlis Roy H

Abstract excerpt

BACKGROUND: Relying on diagnostic categories of neuropsychiatric illness obscures the complexity of these disorders. Capturing multiple dimensional measures of neuropathology could facilitate the clinical and neurobiological investigation of cognitive and behavioral phenotypes. METHODS: We developed a natural language processing-based approach to extract five symptom dimensions, based on the National Institute of...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Cohort Studies
Share to Electronic Health Records

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Hospitalization

Share to Mental Disorders

Share to Natural Language Processing

Share to Neuropsychological Tests

Share to Psychiatric Status Rating Scales

Share to Psychopathology

Source

Open in PubMed Open full text

Identifiers

PMID: 29496195
DOI: 10.1016/j.biopsych.2018.01.011
PMCID: PMC5972065

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

High Throughput Phenotyping for Dimensional Psychopathology in Electronic Health Records.PMID 29496195Read ↗

Mapping of Transdiagnostic Neuropsychiatric Phenotypes Across Patients in Two General Hospitals.Semantic proximity Read ↗

Identifying phenotypic signatures of neuropsychiatric disorders from electronic medical records.Semantic proximity Read ↗

Genome-wide Association Study of Dimensional Psychopathology Using Electronic Health Records.Semantic proximity Read ↗

Phecoder: semantic retrieval for auditing and expanding ICD-based phenotypes in EHR biobanksSemantic proximity Read ↗

Dimensional clinical phenotyping using post-mortem brain donor medical records: Association with neuropathologySemantic proximity Read ↗

Integrating questionnaire measures for transdiagnostic psychiatric phenotyping using word2vec.Semantic proximity Read ↗

Characterizing Dementia Phenotypes from Unstructured EHR Notes with Generative AI and Interpretable Machine LearningSemantic proximity Read ↗

Natural language processing diagnosed behavioural disturbance phenotypes in the intensive care unit: characteristics, prevalence, trajectory, treatment, and outcomes.Semantic proximity Read ↗

Natural Language Processing (NLP) based verbal fluency markers as differential diagnostic indicators of early psychotic, affective and clinical high-risk statesSemantic proximity Read ↗

Symptom-based phenotype discovery in motor neuron disease using natural language processing of electronic health recordsSemantic proximity Read ↗

Evaluating Large Language Models for Assessment of Psychosis RiskSemantic proximity Read ↗

Case-control study of neuropsychiatric symptoms following COVID-19 hospitalization in 2 academic health systemsSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.