@inproceedings{2a96a79121f44b38ae373cf79c961057,
title = "Data Analytics of Electronic Medical Record to Study Racial Diversities in Cardiovascular Diagnosis and Treatment",
abstract = "The study of precision medicine that measures the effects of social, cultural, and environmental influences on health is essential to improve health outcomes. Race is a social concept used historically to divide, track, control populations, and reinforce social hierarchies. Beyond genetics, race is also a surrogate for other socioeconomic factors affecting patient outcomes. Our data analytics study aims to analyze the Electronic Medical Record (EMR) to study patients of different races in diagnosing and treating Coronary Artery Disease (CAD). We found no race discrepancies at the University of California San Francisco Medical Centers. This study opens several new hypotheses for further research in this crucial field.",
keywords = "Cardiovascular Disease, Data Analytics, Electronic Medical Record, Precision Medicine, Racial Study",
author = "Maryam Panahiazar and Yorick Chern and Ramon Riojas and Latif, {Omar S.} and Dexter Hadley and Beygui, {Ramin E.}",
note = "Publisher Copyright: {\textcopyright} 2022 European Federation for Medical Informatics (EFMI) and IOS Press.; 32nd Medical Informatics Europe Conference, MIE 2022 ; Conference date: 27-05-2022 Through 30-05-2022",
year = "2022",
month = may,
day = "25",
doi = "10.3233/SHTI220519",
language = "English (US)",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press BV",
pages = "550--554",
editor = "Brigitte Seroussi and Patrick Weber and Ferdinand Dhombres and Cyril Grouin and Jan-David Liebe and Jan-David Liebe and Jan-David Liebe and Sylvia Pelayo and Andrea Pinna and Bastien Rance and Bastien Rance and Lucia Sacchi and Adrien Ugon and Adrien Ugon and Arriel Benis and Parisis Gallos",
booktitle = "Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022",
address = "Netherlands",
}