Artificial Intelligence in Hypertension Management: An Ace up Your Sleeve

Author:

Visco Valeria1ORCID,Izzo Carmine1ORCID,Mancusi Costantino2ORCID,Rispoli Antonella1,Tedeschi Michele1,Virtuoso Nicola3,Giano Angelo1,Gioia Renato1,Melfi Americo3,Serio Bianca4,Rusciano Maria Rosaria1ORCID,Di Pietro Paola1ORCID,Bramanti Alessia1,Galasso Gennaro1ORCID,D’Angelo Gianni5ORCID,Carrizzo Albino16ORCID,Vecchione Carmine16,Ciccarelli Michele1ORCID

Affiliation:

1. Department of Medicine, Surgery and Dentistry, University of Salerno, 84081 Baronissi, Italy

2. Department of Advanced Biomedical Sciences, Federico II University of Naples, 80138 Naples, Italy

3. Cardiology Unit, University Hospital “San Giovanni di Dio e Ruggi d’Aragona”, 84131 Salerno, Italy

4. Hematology and Transplant Center, University Hospital “San Giovanni di Dio e Ruggi d’Aragona”, 84131 Salerno, Italy

5. Department of Computer Science, University of Salerno, 84084 Fisciano, Italy

6. Vascular Physiopathology Unit, IRCCS Neuromed, 86077 Pozzilli, Italy

Abstract

Arterial hypertension (AH) is a progressive issue that grows in importance with the increased average age of the world population. The potential role of artificial intelligence (AI) in its prevention and treatment is firmly recognized. Indeed, AI application allows personalized medicine and tailored treatment for each patient. Specifically, this article reviews the benefits of AI in AH management, pointing out diagnostic and therapeutic improvements without ignoring the limitations of this innovative scientific approach. Consequently, we conducted a detailed search on AI applications in AH: the articles (quantitative and qualitative) reviewed in this paper were obtained by searching journal databases such as PubMed and subject-specific professional websites, including Google Scholar. The search terms included artificial intelligence, artificial neural network, deep learning, machine learning, big data, arterial hypertension, blood pressure, blood pressure measurement, cardiovascular disease, and personalized medicine. Specifically, AI-based systems could help continuously monitor BP using wearable technologies; in particular, BP can be estimated from a photoplethysmograph (PPG) signal obtained from a smartphone or a smartwatch using DL. Furthermore, thanks to ML algorithms, it is possible to identify new hypertension genes for the early diagnosis of AH and the prevention of complications. Moreover, integrating AI with omics-based technologies will lead to the definition of the trajectory of the hypertensive patient and the use of the most appropriate drug. However, AI is not free from technical issues and biases, such as over/underfitting, the “black-box” nature of many ML algorithms, and patient data privacy. In conclusion, AI-based systems will change clinical practice for AH by identifying patient trajectories for new, personalized care plans and predicting patients’ risks and necessary therapy adjustments due to changes in disease progression and/or therapy response.

Funder

Italian Ministry of Economic Development

Publisher

MDPI AG

Subject

Pharmacology (medical),General Pharmacology, Toxicology and Pharmaceutics

Reference103 articles.

1. Sorriento, D., Rusciano, M.R., Visco, V., Fiordelisi, A., Cerasuolo, F.A., Poggio, P., Ciccarelli, M., and Iaccarino, G. (2021). The Metabolic Role of GRK2 in Insulin Resistance and Associated Conditions. Cells, 10.

2. Larger Blood Pressure Reduction by Fixed-Dose Compared to Free Dose Combination Therapy of ACE Inhibitor and Calcium Antagonist in Hypertensive Patients;Visco;Transl. Med. UniSa,2017

3. NCD Risk Factor Collaboration (2017). Worldwide trends in blood pressure from 1975 to 2015: A pooled analysis of 1479 population-based measurement studies with 19.1 million participants. Lancet, 389, 37–55.

4. Izzo, C., Vitillo, P., Di Pietro, P., Visco, V., Strianese, A., Virtuoso, N., Ciccarelli, M., Galasso, G., Carrizzo, A., and Vecchione, C. (2021). The Role of Oxidative Stress in Cardiovascular Aging and Cardiovascular Diseases. Life, 11.

5. 2003 World Health Organization (WHO)/International Society of Hypertension (ISH) statement on management of hypertension;Whitworth;J. Hypertens.,2003

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3