Last Update Date: Sep 07, 2020
- Prognostic accuracy of emergency department triage tools for adults with suspected COVID-19: The PRIEST observational cohort study
B Thomas et al, MEDRXIV, September 7, 2020 - Application of Machine Learning Methods in Nursing Home Research.
Lee Soo-Kyoung et al. International journal of environmental research and public health 2020 Aug 17(17) - [Epidemiological characteristics of COVID-19 monitoring cases in Yinzhou district based on health big data platform].
Sun Y X et al. Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi 2020 Aug 41(8) 1220-1224 - Understanding the stakeholders' preferences on a mobile application to reduce door to balloon time in the management of ST-elevated myocardial infarction patients - a qualitative study.
Alkamel Nour et al. BMC medical informatics and decision making 2020 Aug 20(1) 205 - Comparison of machine learning techniques to predict unplanned readmission following total shoulder arthroplasty.
Arvind Varun et al. Journal of shoulder and elbow surgery 2020 Jun - The Byzantine Role of Big Data Application in Nursing Science: A Systematic Review.
Caruso Rosario et al. Computers, informatics, nursing : CIN 2020 Aug - Constipation Predominant Irritable Bowel Syndrome and Functional Constipation Are Not Discrete Disorders: A Machine Learning Approach.
Ruffle James K et al. The American journal of gastroenterology 2020 Aug - Use of artificial intelligence in computed tomography dose optimisation.
McCollough C H et al. Annals of the ICRP 2020 Sep 146645320940827 - Assessment of a Deep Learning Model to Predict Hepatocellular Carcinoma in Patients With Hepatitis C Cirrhosis.
Ioannou George N et al. JAMA network open 2020 Sep 3(9) e2015626 - Transforming machine translation: a deep learning system reaches news translation quality comparable to human professionals.
Popel Martin et al. Nature communications 2020 Sep 11(1) 4381 - GENERALIZABLE MULTI-SITE TRAINING AND TESTING OF DEEP NEURAL NETWORKS USING IMAGE NORMALIZATION.
Onofrey John A et al. Proceedings. IEEE International Symposium on Biomedical Imaging 2019 Apr 2019348-351 - Investigating the Attitudes of Adolescents and Young Adults Towards JUUL: Computational Study Using Twitter Data.
Benson Ryzen et al. JMIR public health and surveillance 2020 Sep 6(3) e19975 - A systematic review of radiomics in osteosarcoma: utilizing radiomics quality score as a tool promoting clinical translation.
Zhong Jingyu et al. European radiology 2020 Sep - T1 and T2 MR fingerprinting measurements of prostate cancer and prostatitis correlate with deep learning-derived estimates of epithelium, lumen, and stromal composition on corresponding whole mount histopathology.
Shiradkar Rakesh et al. European radiology 2020 Sep - Classifying the type of delivery from cardiotocographic signals: A machine learning approach.
Ricciardi C et al. Computer methods and programs in biomedicine 2020 Aug 196105712 - Implementation of Artificial Intelligence-Based Clinical Decision Support to Reduce Hospital Readmissions at a Regional Hospital.
Romero-Brufau Santiago et al. Applied clinical informatics 2020 Aug 11(4) 570-577 - Evidence Based Prediction and Progression Monitoring on Retinal Images from Three Nations.
Al Turk Lutfiah et al. Translational vision science & technology 2020 Aug 9(2) 44 - The Evolving Landscape of Myelodysplastic Syndrome Prognostication.
Shreve Jacob et al. Clinical hematology international 2020 Jun 2(2) 43-48 - Harnessing Novel Data Sources and Technologies for the Study of Social Determinants of Health
NHLBI Event, September 29 - 30, 2020 - Social Determinants Associated with COVID-19 Mortality in the United States
S Depopaphaya et al, MEDRXIV, September 3, 2020
Disclaimer: Articles listed in Non-Genomics Precision Health Update are selected by the CDC Office of Public Health Genomics to provide current awareness of the scientific literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the Clips, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.
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