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Advancements and Challenges of AI-Based Tools as an Effective Personalized Medicine in the Future for the Early Diagnosis of Pulmonary Hypertension

Journal of Biomedical Research & Environmental Sciences article abstract with citation details, DOI, publication dates, subject areas, full text links, and references.

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Open Access
Article Type Mini Review
Subject Medicine Group
OCLC JBRES Record
Gayathri Ananthakrishnan*, Matthias Dehmer and Agata Makowska
Issue: Volume6-Issue5
Pages: 400-406
Received: 2025-04-22
Accepted: 2025-05-02
Published: 2025-05-05

Abstract

Personalized medicine is the customizable approach to medical treatment and healthcare decisions for individual patients based on their unique genetic, environmental, and lifestyle factors. Integrating Artificial Intelligence (AI) into personalized medicine could improve this diagnostic trend. AI predictive models have shown significant promise in diagnosing Pulmonary Hypertension (PH). PH is a complex and often underdiagnosed condition associated with significant morbidity and mortality. Early diagnosis, accurate risk stratification, and personalized treatment are critical for improving patient outcomes in this rare disease. Our review primarily focuses on the currently available predictive AI models for the early detection of Pulmonary Hypertension (PH) using electronic health records. We also emphasize the importance of advanced AI tools integrating additional features, such as genomics. Specifically, we discuss the use of machine learning techniques, including both supervised and unsupervised approaches. Despite the potential of AI predictive tools to transform early detection of PH, challenges remain in effectively integrating them into clinical workflows and interpretation. These challenges arise from issues such as the availability of large, unintegrated datasets, unclear definitions of clustered data, a lack of external validation, and the ineffective use of unstructured data, such as clinicians' notes.

FullText HTML FullText PDF DOI: 10.37871/jbres2097 Crossmark

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© 2025 Ananthakrishnan G, et al. Distributed under Creative Commons CC-BY 4.0 Creative CommonsAttribution

How to cite this article

Ananthakrishnan G, Dehmer M, Makowska A. Advancements and Challenges of AI-Based Tools as an Effective Personalized Medicine in the Future for the Early Diagnosis of Pulmonary Hypertension. J Biomed Res Environ Sci. 2025 May 05; 6(5): 400-406. doi: 10.37871/jbres2097, Article ID: JBRES2097, Available at: https://www.jelsciences.com/articles/jbres2097.pdf

Subject area(s)

HypertensionPulmonology

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