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Machine Learning Models to Predict Myocardial Infarction Within 10-Years Follow-up of Cardiovascular Disease Progression.

, , , , , , , and . BHI, page 1-4. IEEE, (2022)

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Machine Learning Models Predict Fatal Myocardial Infarction Within 10-Years Follow-Up Utilizing Explainable AI., , , , , and . BIBE, page 320-324. IEEE, (2023)Machine Learning Models Predict the Need of Amputation and/or Peripheral Artery Revascularization in Hypertensive Patients Within 7-Years Follow-Up., , , , , , , , and . EMBC, page 1-4. IEEE, (2023)EPIQ - efficient detection of SNP-SNP epistatic interactions for quantitative traits., , , , , and . Bioinform., 30 (12): 19-25 (2014)A hybrid data harmonization workflow using word embeddings for the interlinking of heterogeneous cross-domain clinical data structures., , , , , , , , and . BHI, page 1-4. IEEE, (2021)Machine Learning Models for Cardiovascular Disease Events Prediction., , , , , , , and . EMBC, page 1066-1069. IEEE, (2022)Machine Learning Models to Predict Myocardial Infarction Within 10-Years Follow-up of Cardiovascular Disease Progression., , , , , , , and . BHI, page 1-4. IEEE, (2022)Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals., , , , , , , , , and 42 other author(s). BioData Min., 10 (1): 25:1-25:20 (2017)Phenome-wide Association Studies on Cardiovascular Health and Fatty Acids Considering PhenotypeQuality Control Practices for Epidemiological Data., , , , , , and . PSB, page 659-670. (2020)