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

Prediction and evaluation of combination pharmacotherapy using natural language processing, machine learning and patient electronic health records.

Journal of biomedical informatics - 1 Sept 2022

Ding Pingjian, Pan Yiheng, Wang Quanqiu, Xu Rong

Abstract excerpt

Combination pharmacotherapy targets key disease pathways in a synergistic or additive manner and has high potential in treating complex diseases. Computational methods have been developed to identifying combination pharmacotherapy by analyzing large amounts of biomedical data. Existing computational approaches are often underpowered due to their reliance on our limited understanding of disease mechanisms. On the...

Read the complete abstract on PubMed

Topics

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

Share to Digoxin
Share to Drug Combinations

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Electronic Health Records

Share to Hydrochlorothiazide

Share to Hypertension

Share to Machine Learning

Share to Natural Language Processing

Share to Phenotype

Source

Identifiers

PMID: 35985621
DOI: 10.1016/j.jbi.2022.104164

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

Prediction and evaluation of combination pharmacotherapy using natural language processing, machine learning and patient electronic health records.PMID 35985621Read ↗

Mapping drug biology to disease genetics to discover drug impacts on the human phenomeSemantic proximity Read ↗

Network Analysis of Predicted Therapeutic Symptoms in National Health Insurance Herbal PrescriptionsSemantic proximity Read ↗

CombDNF: Disease-specific drug combination predictions with network-based features on clinically validated dataSemantic proximity Read ↗

A knowledge graph approach to discovering drug combination therapies across the phenomeSemantic proximity Read ↗

Disentangling the contribution of disease genes to drug therapeutic and side effectsSemantic proximity Read ↗

Systematic integration of biomedical knowledge prioritizes drugs for repurposingSemantic proximity Read ↗

Shared etiology of Mendelian and complex disease supports drug discoverySemantic proximity Read ↗

Network reinforcement driven drug repurposing for COVID-19 by exploiting disease-gene-drug associationsSemantic proximity Read ↗

Disease comorbidity-guided drug repositioning: a case study in schizophrenia.Semantic proximity Read ↗

Pathway and network embedding methods for prioritizing psychiatric drugsSemantic proximity Read ↗

Identification of disease treatment mechanisms through the multiscale interactomeSemantic proximity Read ↗

Extracting and characterizing gene-drug relationships from the literature.Semantic proximity Read ↗

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