Mohanad Alkhodari, Zhaohan Xiong, Ahsan H Khandoker, Leontios J Hadjileontiadis, Paul Leeson, Winok Lapidaire
{"title":"The role of artificial intelligence in hypertensive disorders of pregnancy: towards personalized healthcare.","authors":"Mohanad Alkhodari, Zhaohan Xiong, Ahsan H Khandoker, Leontios J Hadjileontiadis, Paul Leeson, Winok Lapidaire","doi":"10.1080/14779072.2023.2223978","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Guidelines advise ongoing follow-up of patients after hypertensive disorders of pregnancy (HDP) to assess cardiovascular risk and manage future patient-specific pregnancy conditions. However, there are limited tools available to monitor patients, with those available tending to be simple risk assessments that lack personalization. A promising approach could be the emerging artificial intelligence (AI)-based techniques, developed from big patient datasets to provide personalized recommendations for preventive advice.</p><p><strong>Areas covered: </strong>In this narrative review, we discuss the impact of integrating AI and big data analysis for personalized cardiovascular care, focusing on the management of HDP.</p><p><strong>Expert opinion: </strong>The pathophysiological response of women to pregnancy varies, and deeper insight into each response can be gained through a deeper analysis of the medical history of pregnant women based on clinical records and imaging data. Further research is required to be able to implement AI for clinical cases using multi-modality and multi-organ assessment, and this could expand both knowledge on pregnancy-related disorders and personalized treatment planning.</p>","PeriodicalId":12098,"journal":{"name":"Expert Review of Cardiovascular Therapy","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Expert Review of Cardiovascular Therapy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/14779072.2023.2223978","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/6/21 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: Guidelines advise ongoing follow-up of patients after hypertensive disorders of pregnancy (HDP) to assess cardiovascular risk and manage future patient-specific pregnancy conditions. However, there are limited tools available to monitor patients, with those available tending to be simple risk assessments that lack personalization. A promising approach could be the emerging artificial intelligence (AI)-based techniques, developed from big patient datasets to provide personalized recommendations for preventive advice.
Areas covered: In this narrative review, we discuss the impact of integrating AI and big data analysis for personalized cardiovascular care, focusing on the management of HDP.
Expert opinion: The pathophysiological response of women to pregnancy varies, and deeper insight into each response can be gained through a deeper analysis of the medical history of pregnant women based on clinical records and imaging data. Further research is required to be able to implement AI for clinical cases using multi-modality and multi-organ assessment, and this could expand both knowledge on pregnancy-related disorders and personalized treatment planning.
期刊介绍:
Expert Review of Cardiovascular Therapy (ISSN 1477-9072) provides expert reviews on the clinical applications of new medicines, therapeutic agents and diagnostics in cardiovascular disease. Coverage includes drug therapy, heart disease, vascular disorders, hypertension, cholesterol in cardiovascular disease, heart disease, stroke, heart failure and cardiovascular surgery. The Expert Review format is unique. Each review provides a complete overview of current thinking in a key area of research or clinical practice.