{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["23(1)"],"submitter":["Friedman EE"],"pubmed_abstract":["Introduction
Researchers in the United States have created several models to predict persons most at risk for HIV. Many of these predictive models use data from all persons newly diagnosed with HIV, the majority of whom are men, and specifically men who have sex with men (MSM). Consequently, risk factors identified by these models are biased toward features that apply only to men or capture sexual behaviours of MSM. We sought to create a predictive model for women using cohort data from two major hospitals in Chicago with large opt-out HIV screening programs.Methods
We matched 48 newly diagnosed women to 192 HIV-negative women based on number of previous encounters at University of Chicago or Rush University hospitals. We examined data for each woman for the two years prior"],"journal":["BMC women's health"],"pagination":["313"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10276380"],"repository":["biostudies-literature"],"pubmed_title":["Development of a predictive model for identifying women vulnerable to HIV in Chicago."],"pmcid":["PMC10276380"],"pubmed_authors":["Shankaran S","Devlin SA","Mason JA","Friedman EE","Kishen EB","Sha BE","Ridgway JP"],"additional_accession":[]},"is_claimable":false,"name":"Development of a predictive model for identifying women vulnerable to HIV in Chicago.","description":"Introduction
Researchers in the United States have created several models to predict persons most at risk for HIV. Many of these predictive models use data from all persons newly diagnosed with HIV, the majority of whom are men, and specifically men who have sex with men (MSM). Consequently, risk factors identified by these models are biased toward features that apply only to men or capture sexual behaviours of MSM. We sought to create a predictive model for women using cohort data from two major hospitals in Chicago with large opt-out HIV screening programs.Methods
We matched 48 newly diagnosed women to 192 HIV-negative women based on number of previous encounters at University of Chicago or Rush University hospitals. We examined data for each woman for the two years prior","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Jun","modification":"2025-04-18T20:35:01.147Z","creation":"2025-02-19T00:50:16.322Z"},"accession":"S-EPMC10276380","cross_references":{"pubmed":["37328764"],"doi":["10.1186/s12905-023-02460-7"]}}