Using machine learning to predict cardiovascular risk using self-reported questionnaires: A right, but a long way to go

David Shamia, Doron Zahger

Research output: Contribution to journal › Editorial

Original language	English
Article number	131178
Journal	International Journal of Cardiology
Volume	389
DOIs	https://doi.org/10.1016/j.ijcard.2023.131178
State	Published - 15 Oct 2023

ASJC Scopus subject areas

@article{85c43d0225ed45318f2c96a586d920f7,

title = "Using machine learning to predict cardiovascular risk using self-reported questionnaires: A right, but a long way to go",

author = "David Shamia and Doron Zahger",

year = "2023",

month = oct,

day = "15",

doi = "10.1016/j.ijcard.2023.131178",

language = "English",

volume = "389",

journal = "International Journal of Cardiology",

issn = "0167-5273",

publisher = "Elsevier Ireland Ltd",

}

TY - JOUR

T1 - Using machine learning to predict cardiovascular risk using self-reported questionnaires

T2 - A right, but a long way to go

AU - Shamia, David

AU - Zahger, Doron

PY - 2023/10/15

Y1 - 2023/10/15

UR - http://www.scopus.com/inward/record.url?scp=85165059367&partnerID=8YFLogxK

U2 - 10.1016/j.ijcard.2023.131178

DO - 10.1016/j.ijcard.2023.131178

M3 - Editorial

C2 - 37451431

AN - SCOPUS:85165059367

SN - 0167-5273

VL - 389

JO - International Journal of Cardiology

JF - International Journal of Cardiology

M1 - 131178

ER -