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Akademický článek

Black and Latinx Primary Caregiver Considerations for Developing and Implementing a Machine Learning–Based Model for Detecting Child Abuse and Neglect With Implications for Racial Bias Reduction: Qualitative Interview Study With Primary Caregivers

Autor: Aviv Y Landau, Ashley Blanchard, Nia Atkins, Stephanie Salazar, Kenrick Cato, Desmond U Patton, Maxim Topaz

Publikováno v: JMIR Formative Research, Vol 7, p e40194 (2023)

BackgroundChild abuse and neglect, once viewed as a social problem, is now an epidemic. Moreover, health providers agree that existing stereotypes may link racial and social class issues to child abuse. The broad adoption of electronic health records

Externí odkaz: https://doaj.org/article/d148c8fed7174f56b2cd596060d84dcc

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Akademický článek

Using natural language processing to identify acute care patients who lack advance directives, decisional capacity, and surrogate decision makers.

Autor: Jiyoun Song, Maxim Topaz, Aviv Y Landau, Robert Klitzman, Jingjing Shang, Patricia Stone, Margaret McDonald, Bevin Cohen

Publikováno v: PLoS ONE, Vol 17, Iss 7, p e0270220 (2022)

The prevalence of patients who are Incapacitated with No Evident Advance Directives or Surrogates (INEADS) remains unknown because such data are not routinely captured in structured electronic health records. This study sought to develop and validate

Externí odkaz: https://doaj.org/article/d6e701edef754441954df81911dfb01d

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Developing machine learning-based models to help identify child abuse and neglect: key ethical challenges and recommended solutions

Autor: Aviv Y Landau, Susi Ferrarello, Ashley Blanchard, Kenrick Cato, Nia Atkins, Stephanie Salazar, Desmond U Patton, Maxim Topaz

Publikováno v: J Am Med Inform Assoc

Child abuse and neglect are public health issues impacting communities throughout the United States. The broad adoption of electronic health records (EHR) in health care supports the development of machine learning–based models to help identify chi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::79897ee800695357a86b0eba89c188ec
https://doi.org/10.1093/jamia/ocab286

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Primary caregiver considerations for developing and implementing a machine learning-based model for detecting child abuse and neglect: A qualitative study (Preprint)

Autor: Aviv Y. Landau, Ashley Blanchard, Nia Atkins, Stephanie Salazar, Kenrick Cato, Desmond U. Patton, Maxim Topaz

BACKGROUND Child abuse and neglect, once viewed as a social problem, is now an epidemic. The broad adoption of electronic health records (EHR) in clinical settings offers a new avenue for addressing this epidemic. To improve the development, implemen

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4e9892075fc820869bb3326e4e068637
https://doi.org/10.2196/preprints.40194

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Akademický článek

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Community implications for gun violence prevention during co-occurring pandemics; a qualitative and computational analysis study

Autor: Desmond U. Patton, Nathan Aguilar, Aviv Y. Landau, Chris Thomas, Rachel Kagan, Tianai Ren, Eric Stoneberg, Timothy Wang, Daniel Halmos, Anish Saha, Amith Ananthram, Kathleen McKeown

Publikováno v: Preventive medicine. 165

This study provides insight into New York City residents' perceptions about violence after the outbreak of Coronavirus disease (COVID-19) based on information from communities in New York City Housing Authority (NYCHA) buildings. In this novel analys

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ede0a2401a00a60e980c8d4705c56db1
https://pubmed.ncbi.nlm.nih.gov/36162487

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Considerations for development of child abuse and neglect phenotype with implications for reduction of racial bias: a qualitative study

Autor: Aviv Y Landau, Ashley Blanchard, Kenrick Cato, Nia Atkins, Stephanie Salazar, Desmond U Patton, Maxim Topaz

Publikováno v: J Am Med Inform Assoc

Objective The study provides considerations for generating a phenotype of child abuse and neglect in Emergency Departments (ED) using secondary data from electronic health records (EHR). Implications will be provided for racial bias reduction and the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ba93723d45c645f954dd4ca5e9e9289a
https://pubmed.ncbi.nlm.nih.gov/35024857

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