Last Posted: Oct 08, 2021
- Prediction of incident atrial fibrillation in community-based electronic health records: a systematic review with meta-analysis.
Nadarajah Ramesh et al. Heart (British Cardiac Society) 2021
- Prediction of Incident Atrial Fibrillation in Chronic Kidney Disease: The Chronic Renal Insufficiency Cohort Study.
Zelnick Leila R et al. Clinical journal of the American Society of Nephrology : CJASN 2021 16(7) 1015-1024
- Differential Genomic Profile in TERT, DSP, and FAM13A Between COPD Patients With Emphysema, IPF, and CPFE Syndrome.
Guzmán-Vargas Javier et al. Frontiers in medicine 2021 8725144
- Remote-Management of COPD: Evaluating the Implementation of Digital Innovation to Enable Routine Care (RECEIVER): the protocol for a feasibility and service adoption observational cohort study.
Taylor Anna et al. BMJ open respiratory research 2021 8(1)
- Predicting the survivals and favorable neurologic outcomes after targeted temperature management by artificial neural networks.
Chiu Wei-Ting et al. Journal of the Formosan Medical Association = Taiwan yi zhi 2021
- The cardiovascular phenotype of Chronic Obstructive Pulmonary Disease (COPD): Applying machine learning to the prediction of cardiovascular comorbidities.
Nikolaou Vasilis et al. Respiratory medicine 2021 186106528
- Artificial Intelligence and Machine Learning in Chronic Airway Diseases: Focus on Asthma and Chronic Obstructive Pulmonary Disease.
Feng Yinhe et al. International journal of medical sciences 2021 18(13) 2871-2889
- Identifying acute exacerbations of chronic obstructive pulmonary disease using patient-reported symptoms and cough feature analysis
S Claxton et al, NPJ Digital Medicine, July 2, 2021
- Development and validation of the Tool for Pharmacists to Predict 30-day hospital readmission in patients with Heart Failure (ToPP-HF).
Riester Melissa R et al. American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists 2021
- Automated CT Staging of Chronic Obstructive Pulmonary Disease Severity for Predicting Disease Progression and Mortality with a Deep Learning Convolutional Neural Network.
Hasenstab Kyle A et al. Radiology. Cardiothoracic imaging 2021 3(2) e200477
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Disclaimer: Articles listed in the Public Health Genomics and Precision Health Knowledge Base are selected by the CDC Office of Public Health Genomics to provide current awareness of the 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 update, 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.