{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T00:37:27Z","timestamp":1781311047543,"version":"3.54.1"},"reference-count":39,"publisher":"Oxford University Press (OUP)","issue":"10","license":[{"start":{"date-parts":[[2024,5,25]],"date-time":"2024-05-25T00:00:00Z","timestamp":1716595200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,10,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>Firearm injury research necessitates using data from often-exploited vulnerable populations of Black and Brown Americans. In order to reduce bias against protected attributes, this study provides a theoretical framework for establishing trust and transparency in the use of AI with the general population.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>We propose a Model Facts template that is easily extendable and decomposes accuracy and demographics into standardized and minimally complex values. This framework allows general users to assess the validity and biases of a model without diving into technical model documentation.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Examples<\/jats:title>\n                  <jats:p>We apply the Model Facts template on 2 previously published models, a violence risk identification model and a suicide risk prediction model. We demonstrate the ease of accessing the appropriate information when the data are structured appropriately.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Discussion<\/jats:title>\n                  <jats:p>The Model Facts template is limited in its current form to human based data and biases. Like nutrition facts, it will require educational programs for users to grasp its full utility. Human computer interaction experiments should be conducted to ensure model information is communicated accurately and in a manner that improves user decisions.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>The Model Facts label is the first framework dedicated to establishing trust with end users and general population consumers. Implementation of Model Facts into firearm injury research will provide public health practitioners and those impacted by firearm injury greater faith in the tools the research provides.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/jamia\/ocae102","type":"journal-article","created":{"date-parts":[[2024,5,26]],"date-time":"2024-05-26T15:57:00Z","timestamp":1716739020000},"page":"2414-2421","source":"Crossref","is-referenced-by-count":4,"title":["Nutrition facts, drug facts, and model facts: putting AI ethics into practice in gun violence research"],"prefix":"10.1093","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8729-511X","authenticated-orcid":false,"given":"Jessica","family":"Zhu","sequence":"first","affiliation":[{"name":"Center for Risk and Reliability, Department of Mechanical Engineering, University of Maryland , College Park, MD 20742, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michel","family":"Cukier","sequence":"additional","affiliation":[{"name":"Center for Risk and Reliability, Department of Mechanical Engineering, University of Maryland , College Park, MD 20742, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"suffix":"Jr","given":"Joseph","family":"Richardson","sequence":"additional","affiliation":[{"name":"Department of African American and Africana Studies, University of Maryland , College Park, MD 20742, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,5,25]]},"reference":[{"issue":"7","key":"2024092007523143700_ocae102-B1","doi-asserted-by":"crossref","first-page":"e0270220","DOI":"10.1371\/journal.pone.0270220","article-title":"Using natural language processing to identify acute care patients who lack advance directives, decisional capacity, and surrogate decision makers","volume":"17","author":"Song","year":"2022","journal-title":"PLoS One"},{"key":"2024092007523143700_ocae102-B2","doi-asserted-by":"crossref","first-page":"366","DOI":"10.1016\/j.compbiomed.2017.11.001","article-title":"A survey of machine learning applications in HIV clinical research and care","volume":"91","author":"Bisaso","year":"2017","journal-title":"Comput Biol Med"},{"key":"2024092007523143700_ocae102-B3","author":"Angwin","year":"2016"},{"key":"2024092007523143700_ocae102-B4","author":"Linder","year":"2020"},{"issue":"2","key":"2024092007523143700_ocae102-B5","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1080\/08964289.2019.1630357","article-title":"Whose responsibility is it to dismantle medical mistrust? 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