Zobrazeno 1 - 10 of 10 pro vyhledávání: '"Ayan, Nasir"'
1
Akademický článek
Improving management of hyponatraemia by increasing urine testing in the emergency department
Autor: Nancy L Dawson, Albert Bui, Ryan Hunter, Christian Karime, Maria S Barrios, Nathaniel E Wiest, Ayan Nasir, R Christopher Chase, Samuel M Jones, Varun P Moktan, Jessica G Creager, Ehsan Shirazi, Michael M Mohseni
Publikováno v: BMJ Open Quality, Vol 12, Iss 3 (2023)
Hyponatraemia on hospital admission is associated with increased length of stay, healthcare expenditures and mortality. Urine studies collected before fluid or diuretic administration are essential to diagnose the underlying cause of hyponatraemia, t
Externí odkaz: https://doaj.org/article/1019734c0a1d426a99a742d716bdc7b1
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2
Akademický článek
Reduction in Health Care Facility–Onset Clostridioides difficile Infection: A Quality Improvement Initiative
Autor: Himesh B. Zaver, MD, Varun P. Moktan, MD, Eugene P. Harper, MD, Aman Bali, MD, Ayan Nasir, MD, Carla Foulks, MD, Justin Kuhlman, MD, Max Green, MD, Gillian A. Algan, BS, Heather C. Parth, MPH, Melody Wu-Ballis, BS, Sandra DiCicco, BS, Brenda T. Smith, BS, Ronald N. Owen, BS, Lorraine S. Mai, BS, Sarah L. Spiros, BS, John Griffis, BS, Daphne T. Ramsey Walker, BS, D. Jane Hata, PhD, Justin M. Oring, DO, Harry R. Powers, MD, Wendelyn Bosch, MD
Publikováno v: Mayo Clinic Proceedings: Innovations, Quality & Outcomes, Vol 5, Iss 6, Pp 1066-1074 (2021)
Objective: To reduce health care facility–onset (HCFO) Clostridioides difficile infection (CDI) incidence by improving diagnostic stewardship and reducing the inappropriate testing of C difficile assays. Patients and Methods: A multidisciplinary te
Externí odkaz: https://doaj.org/article/0803db8cd6264022a6cab137fe652613
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4
Akademický článek
A Brief Analysis of Key Machine Learning Methods for Predicting Medicare Payments Related to Physical Therapy Practices in the United States
Autor: Shrirang A. Kulkarni, Jodh S. Pannu, Andriy V. Koval, Gabriel J. Merrin, Varadraj P. Gurupur, Ayan Nasir, Christian King, Thomas T. H. Wan
Publikováno v: Information, Vol 12, Iss 2, p 57 (2021)
Background and objectives: Machine learning approaches using random forest have been effectively used to provide decision support in health and medical informatics. This is especially true when predicting variables associated with Medicare reimbursem
Externí odkaz: https://doaj.org/article/54a4a0699225410a874d70a3082d00a4
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6
A Brief Analysis of Key Machine Learning Methods for Predicting Medicare Payments Related to Physical Therapy Practices in the United States
Autor: Jodh Singh Pannu, Andriy Koval, Ayan Nasir, Shrirang Ambaji Kulkarni, Gabriel J. Merrin, Varadraj P. Gurupur, Thomas T. H. Wan, Christian King
Publikováno v: Information
Volume 12
Issue 2
Information, Vol 12, Iss 57, p 57 (2021)
Background and objectives: Machine learning approaches using random forest have been effectively used to provide decision support in health and medical informatics. This is especially true when predicting variables associated with Medicare reimbursem
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3168b6e99fc116c91a72a8a34d7a2034
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7
Analysing the power of deep learning techniques over the traditional methods using medicare utilisation and provider data
Autor: Xinliang Liu, Shrirang Ambaji Kulkarni, Varadraj P. Gurupur, Ayan Nasir, Usha Desai
Publikováno v: Journal of Experimental & Theoretical Artificial Intelligence. 31:99-115
Deep Learning Technique (DLT) is the sub-branch of Machine Learning (ML) which assists to learn the data in multiple levels of representation and abstraction and shows impressive performance on man...
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::123001cbf91324ec342fd53d6d7098cf
https://doi.org/10.1080/0952813x.2018.1518999
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9
Disparities in patient record completeness with respect to the health care utilization project
Autor: Xinliang Liu, Varadraj P. Gurupur, Zaeem Qureshi, Ayan Nasir
Publikováno v: Health informatics journal. 25(2)
Patient data completeness is an important characteristic in maintaining accurate health records and providing the highest standard of care. Furthermore, finding discrepancies in care based on different subpopulation parameters is important to identif
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b8f12f7f184e3513a04e2206f24f64e4
https://pubmed.ncbi.nlm.nih.gov/28789583
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10
Akademický článek
Disparities in patient record completeness with respect to the health care utilization project.
Autor: Ayan Nasir1, Xinliang Liu1, Gurupur, Varadraj1 varadraj.gurupur@ucf.edu, Zaeem Qureshi2
Publikováno v: Health Informatics Journal. Jun2019, Vol. 25 Issue 2, p401-416. 16p.
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