Jianli Zhong

Hainan Institute of Biotechnology, Haikou, 570206, Hainan, China
Author    Correspondence author
Bioscience Methods, 2024, Vol. 15, No. 3   doi: 10.5376/bm.2024.15.0014
Received: 09 Apr., 2024    Accepted: 24 May, 2024    Published: 13 Jun., 2024

This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Zhong J.L., 2024, Development of ai-based diagnostic systems for hypertensive heart disease, Bioscience Methods, 15(3): 124-138 (doi: 10.5376/bm.2024.15.0014)

The development of AI-based diagnostic systems for hypertensive heart disease represents a significant advancement in cardiovascular medicine. This study explores the integration of artificial intelligence (AI) and machine learning (ML) technologies in the diagnosis, prediction, and management of hypertensive heart disease. AI applications, particularly deep learning (DL) and machine learning algorithms, have shown promise in enhancing diagnostic accuracy, personalizing treatment plans, and predicting disease progression. Wearable devices and mobile technologies equipped with AI capabilities enable continuous monitoring and early detection of hypertension-related complications. Despite the transformative potential, challenges such as data privacy, algorithm transparency, and the need for high-quality data remain. This study synthesizes recent research findings, highlighting the benefits and limitations of AI in hypertensive heart disease management, and underscores the importance of ongoing methodological advancements to fully realize the potential of AI in clinical practice.

Artificial intelligence; Hypertensive heart disease; Machine learning; Diagnostic systems; Cardiovascular medicine