TY - JOUR
T1 - The role of artificial intelligence in hypertensive disorders of pregnancy
T2 - towards personalized healthcare
AU - Alkhodari, Mohanad
AU - Xiong, Zhaohan
AU - Khandoker, Ahsan H.
AU - Hadjileontiadis, Leontios J.
AU - Leeson, Paul
AU - Lapidaire, Winok
N1 - Publisher Copyright:
© 2023 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - artificial intelligence
KW - deep learning
KW - Hypertension disorders of pregnancy
KW - machine learning
KW - personalized medicine
KW - preeclampsia
UR - http://www.scopus.com/inward/record.url?scp=85164063045&partnerID=8YFLogxK
U2 - 10.1080/14779072.2023.2223978
DO - 10.1080/14779072.2023.2223978
M3 - Review article
C2 - 37300317
AN - SCOPUS:85164063045
SN - 1477-9072
VL - 21
SP - 531
EP - 543
JO - Expert Review of Cardiovascular Therapy
JF - Expert Review of Cardiovascular Therapy
IS - 7
ER -