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Precision Health Database


Precision Health Database|Search|PHGKB

Last data update: Dec 02, 2023. (Total: 62228 Documents since 2012)
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A deep learning and radiomics based Alberta stroke program early CT score method on CTA to evaluate acute ischemic stroke.
Ting Fang et al. J Xray Sci Technol 2023
Deep learning-based NT-proBNP prediction from the ECG for risk assessment in the community.
Meraj Neyazi et al. Clin Chem Lab Med 2023
Machine learning-based prediction of symptomatic intracerebral hemorrhage after intravenous thrombolysis for stroke: a large multicenter study.
Rui Wen et al. Front Neurol 2023 141247492
Machine learning applications in stroke medicine: advancements, challenges, and future prospectives.
Mario Daidone et al. Neural Regen Res 2023 19(4) 769-773
[Establishment and evaluation of a predictive model for early neurological deterioration after intravenous thrombolysis in acute ischemic stroke based on machine learning].
Zhe Lyu et al. Zhonghua Wei Zhong Bing Ji Jiu Yi Xue 2023 35(9) 945-950
Predicting Major Adverse Cardiovascular Events Following Carotid Endarterectomy Using Machine Learning.
Ben Li et al. J Am Heart Assoc 2023 e030508
Explainable Risk Prediction of Post-Stroke Adverse Mental Outcomes Using Machine Learning Techniques in a Population of 1780 Patients.
Chien Wei Oei et al. Sensors (Basel) 2023 23(18)
An artificial intelligence-based prognostic prediction model for hemorrhagic stroke.
Yihao Chen et al. Eur J Radiol 2023 167111081
Using Neural Networks Algorithm in Ischemic Stroke Diagnosis: A Systematic Review.
Suebsarn Ruksakulpiwat et al. J Multidiscip Healthc 2023 162593-2602
Combinatorial Use of Machine Learning and Logistic Regression for Predicting Carotid Plaque Risk Among 5.4 Million Adults With Fatty Liver Disease Receiving Health Check-Ups: Population-Based Cross-Sectional Study.
Yuhan Deng et al. JMIR Public Health Surveill 2023 9e47095
Automated ASPECTS calculation may equal the performance of experienced clinicians: a machine learning study based on a large cohort.
Shu Wan et al. Eur Radiol 2023
Development and validation of a machine learning-based prognostic risk stratification model for acute ischemic stroke.
Kai Wang et al. Sci Rep 2023 13(1) 13782
Interpretable machine learning for predicting 28-day all-cause in-hospital mortality for hypertensive ischemic or hemorrhagic stroke patients in the ICU: a multi-center retrospective cohort study with internal and external cross-validation.
Jian Huang et al. Front Neurol 2023 141185447
Comparing Explainable Machine Learning Approaches With Traditional Statistical Methods for Evaluating Stroke Risk Models: Retrospective Cohort Study.
Sermkiat Lolak et al. JMIR Cardio 2023 7e47736
Prediction of subjective cognitive decline after corpus callosum infarction by an interpretable machine learning-derived early warning strategy.
Yawen Xu et al. Front Neurol 2023 141123607
Predicting new-onset post-stroke depression from real-world data using machine learning algorithm.
Yu-Ming Chen et al. Front Psychiatry 2023 141195586
Cardiovascular disease/stroke risk stratification in deep learning framework: a review.
Mrinalini Bhagawati et al. Cardiovasc Diagn Ther 2023 13(3) 557-598
Using Artificial Intelligence in Predicting Ischemic Stroke Events After Percutaneous Coronary Intervention.
Chieh-Ju Chao et al. J Invasive Cardiol 2023 35(6) E297-E311
Development and validation of an interpretable machine learning model-Predicting mild cognitive impairment in a high-risk stroke population.
Feng-Juan Yan et al. Front Aging Neurosci 2023 151180351
Automatic Alberta Stroke Program Early Computed Tomographic Scoring in patients with acute ischemic stroke using diffusion-weighted imaging.
Yan Wu et al. Med Biol Eng Comput 2023
Cardiovascular disease (CVD) outcomes and associated risk factors in a medicare population without prior CVD history: an analysis using statistical and machine learning algorithms.
Gregory Yoke Hong Lip et al. Intern Emerg Med 2023 1-11
Social bias in artificial intelligence algorithms designed to improve cardiovascular risk assessment relative to the Framingham Risk Score: a protocol for a systematic review.
Ivneet Garcha et al. BMJ Open 2023 13(5) e067638
Development and validation of explainable machine-learning models for carotid atherosclerosis early screening.
Ke Yun et al. J Transl Med 2023 21(1) 353
Interpretable Machine Learning Model Predicting Early Neurological Deterioration in Ischemic Stroke Patients Treated with Mechanical Thrombectomy: A Retrospective Study.
Tongtong Yang et al. Brain Sci 2023 13(4)
Machine learning for the prediction of cognitive impairment in older adults.
Wanyue Li et al. Front Neurosci 2023 171158141
Artificial neural network machine learning prediction of the smoking behavior and health risks perception of Indonesian health professionals.
Desy Nuryunarsih et al. Environ Anal Health Toxicol 2023 38(1) e2023003-0
Defining the Age of Young Ischemic Stroke Using Data-Driven Approaches.
Vida Abedi et al. J Clin Med 2023 12(7)
A Hybrid Stacked CNN and Residual Feedback GMDH-LSTM Deep Learning Model for Stroke Prediction Applied on Mobile AI Smart Hospital Platform.
Bassant M Elbagoury et al. Sensors (Basel) 2023 23(7)
A machine learning model for visualization and dynamic clinical prediction of stroke recurrence in acute ischemic stroke patients: A real-world retrospective study.
Kai Wang et al. Front Neurosci 2023 171130831
Prediction of blood pressure variability during thrombectomy using supervised machine learning and outcomes of patients with ischemic stroke from large vessel occlusion.
Daniel Najafali et al. J Thromb Thrombolysis 2023
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