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Specialty: Cardiology
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Total 295 results found since Jan 2013.
Using Artificial Intelligence in Predicting Ischemic Stroke Events After Percutaneous Coronary Intervention
CONCLUSIONS: The RF model accurately predicts short- and long-term risk of IS and outperforms logistic regression analysis in patients undergoing PCI. Patients with periprocedural stroke may benefit from aggressive management to reduce the future risk of IS.PMID:37410747
Source: The Journal of Invasive Cardiology - July 6, 2023 Category: Cardiology Authors: Chieh-Ju Chao Pradyumna Agasthi Timothy Barry Chia-Chun Chiang Panwen Wang Hasan Ashraf Farouk Mookadam Amith R Seri Nithin Venepally Mohamed Allam Sai Harika Pujari Anil Sriramoju Mohamed Sleem Said Alsidawi Mackram Eleid Nirat Beohar Floyd D Fortuin Eri Source Type: research
A comparative effectiveness study of carotid intervention for long-term stroke prevention in patients with severe asymptomatic stenosis from a large integrated health system
CONCLUSIONS: In this contemporary cohort study of patients with ACS utilizing rigorous analytic methodology, CEA appears to have a small but statistically significant effect on stroke prevention out to 8 years. Further study is needed to appropriately select the subset of patients most likely to benefit from intervention.PMID:37406943 | DOI:10.1016/j.jvs.2023.06.024
Source: Atherosclerosis - July 5, 2023 Category: Cardiology Authors: Robert W Chang Noel Pimentel Lue-Yen Tucker Kara A Rothenberg Andrew L Avins Alexander C Flint Rishad M Faruqi Mai N Nguyen-Huynh Romain Neugebauer Source Type: research
Prediction of short-term atrial fibrillation risk using primary care electronic health records
Conclusions
FIND-AF, a machine learning algorithm applicable at scale in routinely collected primary care data, identifies people at higher risk of short-term AF.
Source: Heart - June 26, 2023 Category: Cardiology Authors: Nadarajah, R., Wu, J., Hogg, D., Raveendra, K., Nakao, Y. M., Nakao, K., Arbel, R., Haim, M., Zahger, D., Parry, J., Bates, C., Cowan, C., Gale, C. P. Tags: Open access, Editor's choice Arrhythmias and sudden death Source Type: research
Development and validation of a prediction model to predict major adverse cardiovascular events in elderly patients undergoing noncardiac surgery: A retrospective cohort study
CONCLUSIONS: This prediction model based on the traditional method could accurately predict the risk of MACEs after noncardiac surgery in elderly patients.PMID:37315395 | DOI:10.1016/j.atherosclerosis.2023.06.008
Source: Atherosclerosis - June 14, 2023 Category: Cardiology Authors: Kai Zhang Chang Liu Xiaoling Sha Siyi Yao Zhao Li Yao Yu Jingsheng Lou Qiang Fu Yanhong Liu Jiangbei Cao Jiaqiang Zhang Yitian Yang Weidong Mi Hao Li Source Type: research
Development of gene model combined with machine learning technology to predict for advanced atherosclerotic plaques
CONCLUSION: In present study, our prediction model was established and showed satisfactory predictive power in both training and test datasets. In addition, this is the first study adopted bioinformatics methods combined with machine learning techniques (RF and ANN) to explore and predict for the advanced atherosclerotic plaques. However, further investigations were needed to verify the screened DEGs and predictive effectiveness of this model.PMID:37315377 | DOI:10.1016/j.clineuro.2023.107819
Source: Atherosclerosis - June 14, 2023 Category: Cardiology Authors: Lufeng Wang Yiwen Bao Fei Yu Wenxia Zhu Jun Lang Wang Jie Yang Hongrong Xie Dongya Huang Source Type: research
Development and validation of a prediction model to predict major adverse cardiovascular events in elderly patients undergoing noncardiac surgery: A retrospective cohort study
CONCLUSIONS: This prediction model based on the traditional method could accurately predict the risk of MACEs after noncardiac surgery in elderly patients.PMID:37315395 | DOI:10.1016/j.atherosclerosis.2023.06.008
Source: Atherosclerosis - June 14, 2023 Category: Cardiology Authors: Kai Zhang Chang Liu Xiaoling Sha Siyi Yao Zhao Li Yao Yu Jingsheng Lou Qiang Fu Yanhong Liu Jiangbei Cao Jiaqiang Zhang Yitian Yang Weidong Mi Hao Li Source Type: research
Development of gene model combined with machine learning technology to predict for advanced atherosclerotic plaques
CONCLUSION: In present study, our prediction model was established and showed satisfactory predictive power in both training and test datasets. In addition, this is the first study adopted bioinformatics methods combined with machine learning techniques (RF and ANN) to explore and predict for the advanced atherosclerotic plaques. However, further investigations were needed to verify the screened DEGs and predictive effectiveness of this model.PMID:37315377 | DOI:10.1016/j.clineuro.2023.107819
Source: Atherosclerosis - June 14, 2023 Category: Cardiology Authors: Lufeng Wang Yiwen Bao Fei Yu Wenxia Zhu Jun Lang Wang Jie Yang Hongrong Xie Dongya Huang Source Type: research
Machine learning-based identification of symptomatic carotid atherosclerotic plaques with dual-energy computed tomography angiography
CONCLUSION: FF and NID can serve as useful imaging markers of symptomatic carotid plaques. This tree-based machine learning model incorporating both DECT and clinical features could potentially comprise a non-invasive method for identification of symptomatic carotid plaques to guide clinical treatment strategies.PMID:37290153 | DOI:10.1016/j.jstrokecerebrovasdis.2023.107209
Source: Atherosclerosis - June 8, 2023 Category: Cardiology Authors: Ling-Jie Wang Pei-Qing Zhai Li-Li Xue Cai-Yun Shi Qian Zhang Hua Zhang Source Type: research
Association of brain microbleeds with risk factors, cognition, and MRI markers in MESA
DISCUSSION: Results suggest differing associations for lobar versus deep locations. Sensitive microbleed quantification will facilitate future longitudinal studies of their potential role as an early indicator of vascular pathology.PMID:37289978 | DOI:10.1002/alz.13346
Source: Atherosclerosis - June 8, 2023 Category: Cardiology Authors: Paul N Jensen Tanweer Rashid Jeffrey B Ware Yuhan Cui Colleen M Sitlani Thomas R Austin W T Longstreth Alain G Bertoni Elizabeth Mamourian R Nick Bryan Ilya M Nasrallah Mohamad Habes Susan R Heckbert Source Type: research
Plain language summary of results from ORION-10 and ORION-11: Two studies to learn how well inclisiran works in people with high cholesterol
Future Cardiol. 2023 Jun 6. doi: 10.2217/fca-2022-0133. Online ahead of print.ABSTRACTWHAT IS THIS PLAIN LANGUAGE SUMMARY ABOUT?: This is a summary of the article describing the results of the ORION-10 and ORION-11 studies, which was published in the New England Journal of Medicine in April 2020. The studies included adult participants with atherosclerotic cardiovascular disease (ASCVD). ASCVD happens when the blood vessels that carry blood from the heart to other areas of the body are blocked by fatty build-up (plaque) causing a heart attack, stroke, or other problems. High levels of low-density lipoprotein cholesterol (L...
Source: Atherosclerosis - June 7, 2023 Category: Cardiology Authors: Kausik K Ray R Scott Wright Source Type: research
Development and validation of explainable machine-learning models for carotid atherosclerosis early screening
CONCLUSIONS: The ML models developed could provide good performance for CAS identification using routine health check-up indicators and could hopefully be applied in scenarios without ethnic and geographic heterogeneity for CAS prevention.PMID:37246225 | DOI:10.1186/s12967-023-04093-8
Source: Atherosclerosis - May 28, 2023 Category: Cardiology Authors: Ke Yun Tao He Shi Zhen Meihui Quan Xiaotao Yang Dongliang Man Shuang Zhang Wei Wang Xiaoxu Han Source Type: research
Machine Learning-Based Prediction of Atrial Fibrillation Risk Using Electronic Medical Records in Older Aged Patients
Atrial fibrillation (AF) is an independent risk factor that increases the risk of stroke 5-fold. The purpose of our study was to develop a 1-year new-onset AF predictive model by machine learning based on 3-year medical information without electrocardiograms in our database to identify AF risk in older aged patients. We developed the predictive model according to the Taipei Medical University clinical research database electronic medical records, including diagnostic codes, medications, and laboratory data.
Source: The American Journal of Cardiology - May 18, 2023 Category: Cardiology Authors: Yung-Ta Kao, Chun-Yao Huang, Yu-Ann Fang, Ju-Chi Liu, Tzu-Hao Chang Source Type: research
Quantitative CTA vascular calcification, atherosclerosis burden, and stroke mechanism in patients with ischemic stroke
CONCLUSION: Atherosclerosis calcium volumes in major vessels were significantly higher in LAA compared to non-LAA stroke in younger age.PMID:37148773 | DOI:10.1016/j.jns.2023.120667
Source: Atherosclerosis - May 6, 2023 Category: Cardiology Authors: Takashi Shimoyama Sibaji Gaj Kunio Nakamura Shivakrishna Kovi Shumei Man Ken Uchino Source Type: research
