Kernel Ridge Regression in Clinical Research

Professor Dr. T.J. Cleophas is internist / clinical pharmacologist / statistician at the educational Albert Schweitzer Hospital Dordrecht Netherlands. He is the writer of many statistics textbooks, and he tutors statistics at the Universities of Amsterdam, Rotterdam, Utrecht, Maastricht, Leiden, Nijmegen, Netherlands. In 2020-2022 he was the invited author and editor of Springer Heidelberg Series on Machine Learning and Statistics Applied to Clinical Studies, which were bought by over 30 million professionals involved in Coronavirus research. He is currently completing an edition entitled "Kernel Ridge Regression in Clinical Research", addressing a novel methodology for big and multidimensiomal data analysis. Professor Dr. A.H. Zwinderman is mathematical PhD, full professor of statistics, and principal investigator at the Academic Medical Center, University of Amsterdam. He authored 663 scientific papers and developed many novel statistical methods with particular focus on omics and big data research. He is co-founder of the sparse canonical methodology for the analysis of data with thousands of predictor variables, and together with Professor Cleophas he contributed to the statistical methods series in the journal Circulation. Much of his current work involves studies based on methodologies like parallel computing, the use of clustercomputers, GPU computing, and grid computing.

1. Traditional Kernel Regression.- 2. Kernel Ridge Regression.- 3. Optimal Scaling vs Kernel Ridge Regression.- 4. Examples of Published Kernel Ridge Regression Research So Far.- 5. Some Terminology.- 6. Effect of Being Blind on Age/Sex Adjusted Mortality Rate, 11630 Patients, Traditional Regressions vs Kernel Ridge Regression.- 7. Effect of Old Treatment on New Treatment, 35 patients, Traditional Regression vs Kernel Ridge Regression.- 8. Effect of Gene Expressions on Drug Efficacy, 250 Patients, Traditional Regressions vs Kernel Ridge Regression.- 9. Effect of Gender, Treatment, and Their Interaction on Numbers of Paroxysmal Atrial Fibrillations, 40 Patients, Traditional Regressions vs Kernel Ridge Regression.- 10. Effect of Laboratory Predictors on Septic Mortality, 200 Patients, Traditional Regressions vs Kernel Ridge Regression.- 11. Effect of Times on C-reactive Protein Levels, 18 Months, Traditional Regressions vs Kernel Ridge Regression.- 12. Effect of Different Dosages of Prednisone and Beta-agonist on Peakflow, 78 Patients, Traditional Regressions vs Kernel Ridge Regression.- 13. Effect of Race, Age, and Gender on Physical Strength, 60 Patients, Traditional Regressions vs Kernel Ridge Regression.- 14. Effect of Treatment, Age, Gender, and Co-morbidity on Hours of Sleep, 20 Patients, Traditional Regressions vs Kernel Ridge Regression.- 15. Effect of Counseling Frequency and Non-compliance on Monthly Stools, 35 Constipated Patients, Traditional Regressions vs Kernel Ridge Regression.- 16. Effect of Treatment Modality, Counseling, and Satisfaction with Doctor on Quality of Life, 450 Patients, Traditional Regressions vs Kernel Ridge Regression.- 17. Effect of Department and Patient Age Class on Risk of Falling out of Bed, 55 Patients, Traditional Regressions vs Kernel Ridge Regression.- 18. Effect of Diet, Gender, Sport, and Medical Treatment on LDL Cholesterol Reduction, 953 Patients, Traditional Regressions vs Kernel Ridge Regression.- 19. Effect of Gender,Age, Weight, and Height on Measured Body Surface, 90 Patients, Traditional Regressions vs Kernel Ridge Regression.- 20. Effect of General Practitioners' Age, Education, and Type of Practice on Lifestyle Advise Given, 139 Physicians, Traditional Regressions vs Kernel Ridge Regression.- 21. Effect of Treatment, Psychological, and Social Scores on numbers of Paroxysmal Atrial Fibrillations, 50 Patients, Traditional Regressions vs Kernel Ridge Regression.- 22. Effects of Various Predictors on Numbers of Convulsions, 3390 Patients, Traditional vs Kernel Ridge Regression.- 23. Effects of Foods Served on Breakfast Taken, 252 Persons, Traditional Regressions and Multinomial Logistic Regression vs Kernel Ridge Regression.- 24. Effect on Anorexia of Personal Factors, 217 Persons, Traditional Regression vs Kernel Ridge Regression.- 25. Effect of Physical Exercise, Calorie Intake, and Their Interaction, on Weight Loss, 64 Patients, Traditional Regressions vs Kernel Ridge Regression.- 26. Summaries.