John Zurowski

ORCID: 0000-0002-2263-6881
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About
Contact & Profiles
Research Areas
  • Elder Abuse and Neglect
  • Health disparities and outcomes
  • AI in cancer detection
  • Patient-Provider Communication in Healthcare
  • Privacy-Preserving Technologies in Data
  • Ethics in Clinical Research
  • Health Literacy and Information Accessibility
  • Chronic Disease Management Strategies
  • Autopsy Techniques and Outcomes
  • Artificial Intelligence in Healthcare and Education
  • Radiomics and Machine Learning in Medical Imaging
  • Global Cancer Incidence and Screening

University of Glasgow
2023

Queen Elizabeth University Hospital
2021

Artificial intelligence (AI) tools may assist breast screening mammography programs, but limited evidence supports their generalizability to new settings. This retrospective study used a 3-year dataset (April 1, 2016-March 31, 2019) from U.K. regional program. The performance of commercially available AI algorithm was assessed with prespecified and site-specific decision threshold evaluate whether its transferable clinical site. consisted women (aged approximately 50-70 years) who attended...

10.1148/ryai.220146 article EN Radiology Artificial Intelligence 2023-03-22

For over a decade, Scotland has implemented and operationalized system of Safe Havens, which provides secure analytics platforms for researchers to access linked, deidentified electronic health records (EHRs) while managing the risk unauthorized reidentification. In this paper, perspective is provided on state-of-the-art Scottish Haven network, including its evolution, define key activities required scale network’s capability facilitate research care improvement initiatives. A set processes...

10.2196/31684 article EN cc-by Journal of Medical Internet Research 2021-12-03

Abstract Objectives To determine factors influencing reader agreement in breast screening and investigate the relationship between level patient outcomes. Methods Reader pair for 83 265 sets of mammograms from Scottish Breast Screening service (2015-2020) was evaluated using Cohen’s kappa statistic. Each mammography examination read by two readers, per routine practice, with second initially blinded but able to choose view first reader’s opinion. If readers disagreed, a third arbitrated....

10.1093/bjr/tqad024 article EN cc-by British Journal of Radiology 2023-12-12

<sec> <title>UNSTRUCTURED</title> For over a decade, Scotland has implemented and operationalized system of Safe Havens, which provides secure analytics platforms for researchers to access linked, deidentified electronic health records (EHRs) while managing the risk unauthorized reidentification. In this paper, perspective is provided on state-of-the-art Scottish Haven network, including its evolution, define key activities required scale network’s capability facilitate research care...

10.2196/preprints.31684 preprint EN 2021-07-09
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