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Artificial intelligence-based classification of cardiac autonomic neuropathy from retinal fundus images in patients with diabetes: The Silesia Diabetes Heart Study.
- Published in:
- Cardiovascular Diabetology, 2024, v. 23, n. 1, p. 1, doi. 10.1186/s12933-024-02367-z
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- Article
Machine Learning Identifies Metabolic Dysfunction–Associated Steatotic Liver Disease in Patients With Diabetes Mellitus.
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- Journal of Clinical Endocrinology & Metabolism, 2024, v. 109, n. 8, p. 2029, doi. 10.1210/clinem/dgae060
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- Article
Artificial intelligence‐enhanced electrocardiogram analysis for identifying cardiac autonomic neuropathy in patients with diabetes.
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- Diabetes, Obesity & Metabolism, 2024, v. 26, n. 7, p. 2624, doi. 10.1111/dom.15578
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- Article
Machine learning profiles of cardiovascular risk in patients with diabetes mellitus: the Silesia Diabetes-Heart Project.
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- Cardiovascular Diabetology, 2023, v. 22, n. 1, p. 1, doi. 10.1186/s12933-023-01938-w
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- Article
Low Quantitative Blush Evaluator score predicts larger infarct size and reduced left ventricular systolic function in patients with STEMI regardless of diabetes status.
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- Scientific Reports, 2023, v. 13, n. 1, p. 1, doi. 10.1038/s41598-022-24855-6
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- Article
Risk factors for cardiovascular disease in patients with metabolic-associated fatty liver disease: a machine learning approach.
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- Cardiovascular Diabetology, 2022, v. 21, n. 1, p. 1, doi. 10.1186/s12933-022-01672-9
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- Article
Influence of SGLT2 Inhibitor Treatment on Urine Antioxidant Status in Type 2 Diabetic Patients: A Pilot Study.
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- Oxidative Medicine & Cellular Longevity, 2021, p. 1, doi. 10.1155/2021/5593589
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- Article