Zobrazeno 1 - 3
of 3
pro vyhledávání: '"John Angiolillo"'
Autor:
Kevin B. Johnson, Sunil Kripalani, Robert M. Cronin, Cosmin Adrian Bejan, Shari L. Barkin, Jill M. Pulley, Robertson Nash, Joshua C. Denny, John Angiolillo, Jana K. Shirey-Rice, Loren Lipworth, Douglas Conway
Publikováno v:
Journal of the American Medical Informatics Association. 25:61-71
ObjectiveUnderstanding how to identify the social determinants of health from electronic health records (EHRs) could provide important insights to understand health or disease outcomes. We developed a methodology to capture 2 rare and severe social d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::48fccb87ed9c425ad7a408b15d0a1ce9
https://doi.org/10.1093/jamia/ocx059
https://doi.org/10.1093/jamia/ocx059
Autor:
Russell L. Rothman, John Angiolillo, S. Trent Rosenbloom, Colin G. Walsh, G. Seibert Tregoning, Melissa L McPheeters
Publikováno v:
Journal of biomedical informatics. 93
Background It remains unclear how to incorporate terminology changes, such as the International Classification of Disease (ICD) transition from ICD-9 to ICD-10, into established automated healthcare quality metrics. Objective To evaluate whether gene
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::80f7dd2b8da66c5d8e0ea096856c4018
https://pubmed.ncbi.nlm.nih.gov/30853653
https://pubmed.ncbi.nlm.nih.gov/30853653
Autor:
Edouard Grave, Chris H. Wiggins, Rimma Pivovarov, John Angiolillo, Noémie Elhadad, Adler J. Perotte
Publikováno v:
J Biomed Inform
Display Omitted We present the UPhenome model, which derives phenotypes in an unsupervised manner.UPhenome scales easily to large sets of diseases and clinical observations.The learned phenotypes combine clinical text, ICD9 codes, lab tests, and medi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::40a4b82e0b64414daa83dbbb0a5b3453