Last Posted: Sep 21, 2021
- Predicting length of stay and mortality among hospitalized patients with type 2 diabetes mellitus and hypertension.
Barsasella Diana et al. International journal of medical informatics 2021 154104569
- Screening for Abdominal Aortic Aneurysms and Risk Factors in 65-Year-Old Men in Oslo, Norway.
Rabben Toril et al. Vascular health and risk management 2021 17561-570
- Clinical Score and Machine Learning-Based Model to Predict Diagnosis of Primary Aldosteronism in Arterial Hypertension.
Buffolo Fabrizio et al. Hypertension (Dallas, Tex. : 1979) 2021 HYPERTENSIONAHA12117444
- Identifying the predictive effectiveness of a genetic risk score for incident hypertension using machine learning methods among populations in rural China.
Niu Miaomiao et al. Hypertension research : official journal of the Japanese Society of Hypertension 2021
- Mobile health technology for diverse populations: challenges and opportunities
JA Diao et al, NPJ Digital Medicine, September 6, 2021
- Familial Hypercholesterolemia-Risk-Score: A New Score Predicting Cardiovascular Events and Cardiovascular Mortality in Familial Hypercholesterolemia.
Paquette Martine et al. Arteriosclerosis, thrombosis, and vascular biology 2021 ATVBAHA121316106
- Implantable loop recorder detection of atrial fibrillation to prevent stroke (The LOOP Study): a randomised controlled trial.
Svendsen Jesper H et al. Lancet (London, England) 2021
- Embryo Screening for Polygenic Disease Risk: Recent Advances and Ethical Considerations.
Tellier Laurent C A M et al. Genes 2021 12(8)
- Predicting 1-Year Mortality after Hip Fracture Surgery: An Evaluation of Multiple Machine Learning Approaches.
Forssten Maximilian Peter et al. Journal of personalized medicine 2021 11(8)
- Improving the Accuracy in Classification of Blood Pressure from Photoplethysmography Using Continuous Wavelet Transform and Deep Learning.
Wu Jiaze et al. International journal of hypertension 2021 20219938584
- LightGBM: an efficient and accurate method for predicting pregnancy diseases.
Liao Hualong et al. Journal of obstetrics and gynaecology : the journal of the Institute of Obstetrics and Gynaecology 2021 1-10
- Yield of Bone Scintigraphy Screening for Transthyretin-related Cardiac Amyloidosis in Different Conditions: Methodological Issues and Clinical Implications.
Tini Giacomo et al. European journal of clinical investigation 2021 e13665
- Evaluation of Effect of Curcumin on Psychological State of Patients with Pulmonary Hypertension by Magnetic Resonance Image under Deep Learning.
Ma Tingting et al. Contrast media & molecular imaging 2021 20219935754
- Development and validation of a model to estimate the risk of acute ischemic stroke in geriatric patients with primary hypertension.
Zheng Xifeng et al. BMC geriatrics 2021 21(1) 458
- Monogenic Diabetes in Youth With Presumed Type 2 Diabetes: Results From the Progress in Diabetes Genetics in Youth (ProDiGY) Collaboration.
Todd Jennifer N et al. Diabetes care 2021
- Machine-Learning-Derived Model for the Stratification of Cardiovascular risk in Patients with Ischemic Stroke.
Ntaios George et al. Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association 2021 30(10) 106018
- Big data-based analysis to characterise and identify variations in the type of Primary Care visits before and during COVID in Catalonia.
Lopez Segui Francesc et al. Journal of medical Internet research 2021
- Mobile health strategies for blood pressure self-management in urban populations with digital barriers: systematic review and meta-analyses
EC Khoong et al, NPJ Digital Medicine, July 22, 2021
- Evaluating the association of social needs assessment data with cardiometabolic health status in a federally qualified community health center patient population.
Drake Connor et al. BMC cardiovascular disorders 2021 21(1) 342
- 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
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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.