Patient characteristics for CVD hospitalization prediction.

Takkavatakarn, Kullaya; Dai, Yang; Wen, Huei Hsun; Kauffman, Justin; Charney, Alexander; Coca, Steven G.; Nadkarni, Girish N.; Chan, Lili

doi:10.1371/journal.pone.0297919.s006

pone.0297919.s006.docx (15.06 kB)

Patient characteristics for CVD hospitalization prediction.

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posted on 2024-02-08, 18:31 authored by Kullaya Takkavatakarn, Yang Dai, Huei Hsun Wen, Justin Kauffman, Alexander Charney, Steven G. Coca, Girish N. Nadkarni, Lili Chan

Patient characteristics for CVD hospitalization prediction.

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whether machine learning using different measures tested several algorithms routinely collected clinical new york city mount sinai bio level social determinants patients &# 8217 machine learning model predicted education outperformed xlink "> area predicted educational attainment level educational attainment implementing ml techniques also significantly higher 77 versus 0 using zip code impact model performance model utilizing survey derived education achieved educational attainment predicted education level education xlink ">significantly higher zip code model relying model incorporating ml model 715 patients derived education zip codes predictive performance highest performance validated questionnaire research instead predicting cardiovascular participant ’individual sdohs home addresses either survey demographic data consequently increase census tracts 67 %.47 %,2 %)

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Patient characteristics for CVD hospitalization prediction.

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