Hypertension Medication Recommendation via Synergistic and Selective Modeling of Heterogeneous Medical Entities: Development and Evaluation Study of a New Model

The findings indicate the superior efficacy of the introduced model in medication recommendation, highlighting its potential to enhance clinical decision-making in the management of hypertension. The code for the model has been released on GitHub.

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Publication Details

Journal
JMIR Medical Informatics
Published
2025-08-29
DOI
https://doi.org/10.2196/74170
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
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article

Hypertension Medication Recommendation via Synergistic and Selective Modeling of Heterogeneous Medical Entities: Development and Evaluation Study of a New Model

Xia Wang, Wei Wang, Zhichang Zhang, Yali Liang et al.
JMIR Medical Informatics
Machine Learning in Healthcare
article

Hypertension Medication Recommendation via Synergistic and Selective Modeling of Heterogeneous Medical Entities: Development and Evaluation Study of a New Model

Xia Wang, Wei Wang, Zhichang Zhang, Yali Liang, Ke Zhang
article en

Abstract

The findings indicate the superior efficacy of the introduced model in medication recommendation, highlighting its potential to enhance clinical decision-making in the management of hypertension. The code for the model has been released on GitHub.

JMIR Medical InformaticsVol. 13
Gansu Provincial Hospital (CN), Northwest Normal University (CN)
Openalex Percentile: Top 88%
Machine Learning in Healthcare
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Hypertension Medication Recommendation via Synergistic and Selective Modeling of Heterogeneous Medical Entities: Development and Evaluation Study of a New Model — Xia Wang, Wei Wang, et al. · JMIR Medical Informatics (2025) | TGRS Research Map | TGRS