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Precision Health Database


Precision Health Database|Search|PHGKB

Heart, Lung, Blood and Sleep Disorders

Last data update: Jun 02, 2023. (Total: 60071 Documents since 2012)
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Development and validation of explainable machine-learning models for carotid atherosclerosis early screening.
Ke Yun et al. J Transl Med 2023 21(1) 353
The contribution of the exposome to the burden of cardiovascular disease.
Thomas Münzel et al. Nat Rev Cardiol 2023
Positional sleep apnea phenotyping using machine learning and digital oximetry biomarkers.
Yuval Ben Sason et al. Physiol Meas
An efficient approach to estimate the risk of coronary artery disease for people living with HIV using machine-learning-based retinal image analysis.
Grace Lui et al. PloS one 2023 18(2) e0281701
Machine learning improves mortality prediction in three-vessel disease.
Xinxing Feng et al. Atherosclerosis 2023 3671-7
Predictive Accuracy of Stroke Risk Prediction Models Across Black and White Race, Sex, and Age Groups.
Chuan Hong et al. JAMA 2023 329(4) 306-317
Using artificial intelligence to study atherosclerosis, predict risk and guide treatments in clinical practice.
Antoniades Charalambos et al. European heart journal 2023
Heterogeneity in the Association Between the Presence of Coronary Artery Calcium and Cardiovascular Events: A Machine Learning Approach in the MESA Study.
Inoue Kosuke et al. Circulation 2022
Rapid lipid-laden plaque identification in intravascular optical coherence tomography imaging based on time-series deep learning.
Rico-Jimenez Jose J et al. Journal of biomedical optics 2022 27(10)
Metabolic syndrome screening in adolescents: New scores AI_METS based on artificial intelligence techniques.
Benmohammed Karima et al. Nutrition, metabolism, and cardiovascular diseases : NMCD 2022
What electronic health records can and cannot tell us in the era of big data.
Bellasi Antonio et al. Atherosclerosis 2022
A machine learning model for non-invasive detection of atherosclerotic coronary artery aneurysm.
Rostam-Alilou Ali A et al. International journal of computer assisted radiology and surgery 2022
Machine Learning-Based Models Incorporating Social Determinants of Health vs Traditional Models for Predicting In-Hospital Mortality in Patients With Heart Failure.
Segar Matthew W et al. JAMA cardiology 2022
Machine Learning Approach for Cardiovascular Risk and Coronary Artery Calcification Score.
Aditya C R et al. BioMed research international 2022 20222632770
Questionnaire-based exposome-wide association studies (ExWAS) reveal expected and novel risk factors associated with cardiovascular outcomes in the Personalized Environment and Genes Study.
Lee Eunice Y et al. Environmental research 2022 113463
Causative Classification of Ischemic Stroke by the Machine Learning Algorithm Random Forests.
Wang Jianan et al. Frontiers in aging neuroscience 2022 14788637
Prediction of 3-year all-cause and cardiovascular cause mortality in a prospective percutaneous coronary intervention registry: Machine learning model outperforms conventional clinical risk scores.
Calburean Paul-Adrian et al. Atherosclerosis 2022 35033-40
Cardiovascular/Stroke Risk Stratification in Parkinson's Disease Patients Using Atherosclerosis Pathway and Artificial Intelligence Paradigm: A Systematic Review.
Suri Jasjit S et al. Metabolites 2022 12(4)
A deep learning model for screening type 2 diabetes from retinal photographs.
Yun Jae-Seung et al. Nutrition, metabolism, and cardiovascular diseases : NMCD 2022
Deep Phenotyping and Prediction of Long-Term Cardiovascular Disease: Optimized by Machine Learning.
Zhuang Xiao-Dong et al. The Canadian journal of cardiology 2022
Analysis of Carotid Ultrasound Screening of High-Risk Groups of Stroke Based on Big Data Technology.
Guo Jiankang et al. Journal of healthcare engineering 2022 20226363691
Artificial Intelligence in Cardiac MRI: Is Clinical Adoption Forthcoming?
Fotaki Anastasia et al. Frontiers in cardiovascular medicine 2022 8818765
ECG-AI: electrocardiographic artificial intelligence model for prediction of heart failure.
Akbilgic Oguz et al. European heart journal. Digital health 2022 2(4) 626-634
Machine Learning Approach to Classify Cardiovascular Disease in Patients With Nonalcoholic Fatty Liver Disease in the UK Biobank Cohort.
Sharma Divya et al. Journal of the American Heart Association 2021 e022576
Machine learning of treadmill exercise test to improve selection for testing for coronary artery disease.
Lee Yin-Hao et al. Atherosclerosis 2021 34023-27
Machine learning models for screening carotid atherosclerosis in asymptomatic adults.
Yu Jian et al. Scientific reports 2021 11(1) 22236
Stratifying the Risk of Cardiovascular Disease in Obstructive Sleep Apnea Using Machine Learning.
Gourishetti Saikrishna C et al. The Laryngoscope 2021
Prediction of Coronary Calcification and Stenosis: Role of Radiomics From Low-Dose CT.
Homayounieh Fatemeh et al. Academic radiology 2021 28(7) 972-979
Automated classification of coronary atherosclerotic plaque in optical frequency domain imaging based on deep learning.
Shibutani Hiroki et al. Atherosclerosis 2021 328100-105
CT ​EvaLuation ​by ​ARtificial ​Intelligence ​For ​Atherosclerosis, Stenosis and Vascular ​MorphologY ​(CLARIFY): ​A ​Multi-center, international study.
Choi Andrew D et al. Journal of cardiovascular computed tomography 2021
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