Endocrine hypertension in 2025: how AI and multiomics are revolutionizing detection

The convergence of multiomics and AI heralds a transformative era in EH care. While proof-of-concept studies demonstrate diagnostic accuracy comparable to invasive tests, translation into routine practice is limited by infrastructural inequities, lack of data harmonization, and gaps in clinician digital literacy. Future efforts should prioritize federated data systems, longitudinal multiomic integration, and hybrid models of human - machine collaboration. Within a decade, endocrine hypertension management will likely evolve from static, phenotype-based diagnosis to dynamic, data-driven systems medicine, integrating continuous biosensing and AI-guided decision support for truly individualized care.

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Publication Details

Journal
Expert Review of Cardiovascular Therapy
Published
2026-02-18
DOI
https://doi.org/10.1080/14779072.2026.2634025
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Endocrine hypertension in 2025: how AI and multiomics are revolutionizing detection

Jeny J Mendoza-Godoy, Juan Eduardo Quiroz-Aldave, Marcio J Concepción-Zavaleta, Juan Carlos Morón-Siguas et al.
Expert Review of Cardiovascular Therapy
Artificial Intelligence in Healthcare and Education
article

Endocrine hypertension in 2025: how AI and multiomics are revolutionizing detection

Jeny J Mendoza-Godoy, Juan Eduardo Quiroz-Aldave, Marcio J Concepción-Zavaleta, Juan Carlos Morón-Siguas, José L Paz-Ibarra, Jenyfer M Fuentes-Mendoza
article en

Abstract

The convergence of multiomics and AI heralds a transformative era in EH care. While proof-of-concept studies demonstrate diagnostic accuracy comparable to invasive tests, translation into routine practice is limited by infrastructural inequities, lack of data harmonization, and gaps in clinician digital literacy. Future efforts should prioritize federated data systems, longitudinal multiomic integration, and hybrid models of human - machine collaboration. Within a decade, endocrine hypertension management will likely evolve from static, phenotype-based diagnosis to dynamic, data-driven systems medicine, integrating continuous biosensing and AI-guided decision support for truly individualized care.

Expert Review of Cardiovascular TherapyVol. 24(3)
National University of San Marcos (PE), Universidad Científica del Sur (PE), Theodore Roosevelt High School (US), University Hospital of Bern (CH), Universidad Nacional de Huancavelica (PE), St Martins Hospital (GB), Universidad Privada de Huancayo "Franklin Roosevelt"
Quality Education
Openalex Percentile: Top 52%
Artificial Intelligence in Healthcare and Education
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