Role of genome-wide association studies, polygenic risk score and AI/ML using big data for personalized treatment to the patients with cardiovascular disease

Journal article

Habiba Abdelhalim, Rachel-Mae Hunter, William DeGroat, Dinesh Mendhe, Saman Zeeshan and Zeeshan Ahmed

Future Medicine AI

11/08/2023

Abstract

Tweetable abstract Role of GWAS, polygenic risk score and AI/ML using big data for personalized treatment to the patients with cardiovascular disease

url

https://doi.org/10.2217/fmai-2023-0018View

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Title: Role of genome-wide association studies, polygenic risk score and AI/ML using big data for personalized treatment to the patients with cardiovascular disease
Creators: Habiba Abdelhalim - Rutgers Institute for Health, Health Care Policy & Aging Research, Rutgers University, 112 Paterson St, New Brunswick, NJ 08901, USA
Rachel-Mae Hunter - Rutgers Institute for Health, Health Care Policy & Aging Research, Rutgers University, 112 Paterson St, New Brunswick, NJ 08901, USA
William DeGroat - Rutgers Institute for Health, Health Care Policy & Aging Research, Rutgers University, 112 Paterson St, New Brunswick, NJ 08901, USA
Dinesh Mendhe - Rutgers Institute for Health, Health Care Policy & Aging Research, Rutgers University, 112 Paterson St, New Brunswick, NJ 08901, USA
Saman Zeeshan - Rutgers Cancer Institute of New Jersey, Rutgers University, 195 Little Albany St, New Brunswick, NJ 08901, USA
Zeeshan Ahmed
Publication Details: Future Medicine AI
Date published: 11/08/2023
Academic Unit: Institute for Health, Health Care Policy and Aging Research
Language: English
Resource Type: Journal article
Identifiers: 991031907005304646