Last Update Date: Aug 24, 2020
- Automatic analysis system of COVID-19 radiographic lung images (XrayCoviDetector)
JN Schlotterbeck et al, MEDRXIV, AUgust 23, 2020 - Associations of comorbidities and medications with COVID-19 outcome: A retrospective analysis of real-world evidence data
B Abou-Jamous et al, MEDRXIV, August 23, 2020 - Health Disparities and COVID-19: A Retrospective Study Examining Individual and Community Factors Causing Disproportionate COVID-19 Outcomes in Cook County, Illinois, March 16-May 31, 2020
L Unruh et al, MEDRXIV, August 24, 2020 - Susceptibility to and transmission of COVID-19 amongst children and adolescents compared with adults: a systematic review and meta-analysis
RM Viner et al, MEDRXIV, August 21, 2020 - Accurately Differentiating COVID-19, Other Viral Infection, and Healthy Individuals Using Multimodal Features via Late Fusion Learning
M XU et al MEDRXIV, August 21, 2020 - A DEEP LEARNING MODEL TO PREDICT THE NEED FOR MECHANICAL VENTILATION USING CHEST X-RAY IMAGES IN HOSPITALIZED COVID-19 PATIENTS
AR Kulkarni et al, MEDRXIV, August 21, 2020 - An SBM-based machine learning model for identifying mild cognitive impairment in patients with Parkinson's disease.
Zhang Jiahui et al. Journal of the neurological sciences 2020 Aug 418117077 - Prediction of respiratory decompensation in Covid-19 patients using machine learning: The READY trial.
Burdick Hoyt et al. Computers in biology and medicine 2020 Aug 124103949 - Demography and Clinical Features of Chalazion Among Patients Seen at a Multi-Tier Eye Care Network in India: An Electronic Medical Records Driven Big Data Analysis Report.
Das Anthony Vipin et al. Clinical ophthalmology (Auckland, N.Z.) 2020 142163-2168 - A Comparison of Three-Dimensional Speckle Tracking Echocardiography Parameters in Predicting Left Ventricular Remodeling.
Zhong Junda et al. Journal of healthcare engineering 2020 20208847144 - Characteristics of Twitter Use by State Medicaid Programs in the United States: Machine Learning Approach.
Zhu Jane M et al. Journal of medical Internet research 2020 Aug 22(8) e18401 - Data Integration Using Advances in Machine Learning in Drug Discovery and Molecular Biology.
Hudson Irene Lena et al. Methods in molecular biology (Clifton, N.J.) 2021 2190167-184 - Using Neural Networks for Relation Extraction from Biomedical Literature.
Sousa Diana et al. Methods in molecular biology (Clifton, N.J.) 2021 2190289-305 - Predicting outdoor ultrafine particle number concentrations, particle size, and noise using street-level images and audio data.
Hong Kris Y et al. Environment international 2020 Aug 144106044 - The Academic Viewpoint on Patient Data Ownership in the Context of Big Data: Scoping Review.
Mirchev Martin et al. Journal of medical Internet research 2020 Aug 22(8) e22214 - Applications of Artificial Intelligence in Musculoskeletal Imaging: From the Request to the Report.
Gorelik Natalia et al. Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes 2020 Aug 846537120947148 - Can Machine Learning Help Identify Patients at Risk for Recurrent Sexually Transmitted Infections?
Elder Heather R et al. Sexually transmitted diseases 2020 Aug - Prognostic machine learning models for COVID-19 to facilitate decision making.
Subudhi Sonu et al. International journal of clinical practice 2020 Aug e13685 - Fully automated endoscopic disease activity assessment in ulcerative colitis.
Yao Heming et al. Gastrointestinal endoscopy 2020 Aug - Using clinical decision support systems to bring predictive models to the glaucoma clinic.
Stagg Brian C et al. Ophthalmology. Glaucoma 2020 Aug
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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