From Promise to Practice: Leveraging Artificial Intelligence to Accelerate Equitable Access to Cancer Screening.
This article focuses on the application of artificial intelligence (AI) in cancer screening and its potential to improve health equity. AI, defined as computer programs that process large datasets and make decisions using algorithms, can enhance cancer screening by enabling personalized risk predict...
| Publicado en: | Public Health Reports Vol. 141; no. 4; pp. 479 - 484 |
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| Autores principales: | , , , , , , , |
| Formato: | Artículo |
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Sage Publications Inc.
Jul/Aug2026
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=194675099&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 194675099 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00333549 PHR jtl: Public Health Reports issn: 00333549 maglogo: Y pubinfo: dt: Jul/Aug2026 vid: 141 iid: 4 pid: 344 pub: Sage Publications Inc. artinfo: ui: 194675099 10.1177/00333549251414401 ppf: 479 ppct: 5 formats: tig: atl: From Promise to Practice: Leveraging Artificial Intelligence to Accelerate Equitable Access to Cancer Screening. aug: au: Housten, Ashley J. Yang, Lin Heckman, Carolyn J. Yeary, Karen Miller, Carrie A. Huh-Yoo, Jina Mullin, Sarah Ko, Linda K. affil: Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St Louis, MO, USA Department of Cancer Epidemiology and Prevention Research, Cancer Care Alberta, Calgary, AB, Canada Department of Oncology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada Behavioral Sciences Section, Department of Medicine, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, USA Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA Department of Family Medicine and Population Health, VCU School of Medicine, Virginia Commonwealth University, Richmond, VA, USA Department of Computer Science, Charles V. Schaefer Jr School of Engineering and Science, Stevens Institute of Technology, Hoboken, NJ, USA Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA Department of Family Medicine, Keck School of Medicine at University of Southern California, Alhambra, CA, USA su: Health services accessibility Community health services Social determinants of health Artificial intelligence Health policy Patient participation Tumor diagnosis Tumor prevention Risk assessment Diagnostic imaging Early detection of cancer Clinical decision support systems Natural language processing Electronic health records sug: subj: Health services accessibility Community health services Social determinants of health Artificial intelligence Health policy Patient participation Residential Mental Health and Substance Abuse Facilities Other Individual and Family Services Other local, municipal and regional public administration Community health centres All Other Outpatient Care Centers Other Electronic and Precision Equipment Repair and Maintenance Diagnostic Imaging Centers Administration of Public Health Programs Tumor diagnosis Tumor prevention Risk assessment Diagnostic imaging Early detection of cancer Clinical decision support systems Natural language processing Electronic health records keyword: artificial intelligence cancer screening health equity artificial intelligence cancer screening health equity ab: This article focuses on the application of artificial intelligence (AI) in cancer screening and its potential to improve health equity. AI, defined as computer programs that process large datasets and make decisions using algorithms, can enhance cancer screening by enabling personalized risk prediction, expediting diagnostic image review, and automating routine tasks, thereby improving access and quality of care across diverse populations. However, challenges such as data bias, lack of transparency, environmental impact, and infrastructure costs must be addressed to prevent exacerbating existing health disparities. The article emphasizes the importance of interdisciplinary collaboration, meaningful engagement with patients and communities, rigorous validation, and ethical oversight to ensure AI tools support rather than replace human judgment and promote equitable cancer screening outcomes. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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