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Akademický článek

Machine Learning Approach to Predict Risk of 90-Day Hospital Readmissions in Patients With Atrial Fibrillation: Implications for Quality Improvement in Healthcare

Autor: Man Hung, Eric S. Hon, Evelyn Lauren, Julie Xu, Gary Judd, Weicong Su

Publikováno v: Health Services Research & Managerial Epidemiology, Vol 7 (2020)

Background: Atrial fibrillation (AF) in the elderly population is projected to increase over the next several decades. Catheter ablation shows promise as a treatment option and is becoming increasingly available. We examined 90-day hospital readmissi

Externí odkaz: https://doaj.org/article/3992877ed8ec43709bfdb6089ba2a229

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Wind Tunnel and Field Evaluation of Trapping Efficiency of Semiochemical Baited Camera-Traps for Capturing Codling Moth (Lepidoptera: Tortricidae)

Autor: Andrew J Frewin, Christopher Adams, Gary Judd, Jordan Hazell

Publikováno v: Journal of economic entomology.

Sex pheromone baited monitoring traps are a critical tool for integrated pest management decisions against many insects, particularly codling moths (Cydia pomonella L.). The addition of cameras for remote monitoring has the potential to enhance the u

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0fc757c9c5195309dc570b40f9a96198
https://pubmed.ncbi.nlm.nih.gov/36102308

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Machine Learning Approach to Predict Risk of 90-Day Hospital Readmissions in Patients With Atrial Fibrillation: Implications for Quality Improvement in Healthcare

Autor: Weicong Su, Gary Judd, Man Hung, Evelyn Lauren, Julie Xu, Eric S. Hon

Publikováno v: Health Services Research and Managerial Epidemiology
Health Services Research & Managerial Epidemiology, Vol 7 (2020)

Background:Atrial fibrillation (AF) in the elderly population is projected to increase over the next several decades. Catheter ablation shows promise as a treatment option and is becoming increasingly available. We examined 90-day hospital readmissio

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5d8e632b797757d86ae628a59d6ccb9a
https://pubmed.ncbi.nlm.nih.gov/33088848

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