J. Tu

Statistics and Probability · Journal of the American Medical Association (JAMA) · 1996–2013

A researcher in the Science corpus: 10 papers; trusts 9 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 20 citations into it; #2,737 of 12,932 by trust here, #6,310 by citations
• Evaluation & Benchmarks — 5 citations into it

Whom J. Tu trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. P. Murtaugh
2. Jr. Frank E. Harrell
3. David W. Hosmer Jr.
4. Peter C. Austin
5. James A. Hanley
6. David Ruppert
7. Esteban Walker
8. Geoffrey E. Hinton
9. Elizabeth R. DeLong
10. Yoav Freund

Who trusts J. Tu overall

1. Isik Yilmaz
2. Binh Thai Pham
3. Ghezlane Halhoul Merabet
4. Peter C. Austin
5. Roger Mundry
6. Feng Xie
7. Travers Ching
8. Biswajeet Pradhan
9. Marco Sandri
10. Courtenay Strong

Papers from J. Tu's perspective

Ordered by how strongly the researchers J. Tu trusts endorse each paper. Same corpus, a different order for every researcher.

1. The Elements of Statistical Learning: Data Mining, Inference, and Prediction
2. Experiments with a New Boosting Algorithm
3. Applied Logistic Regression: Hosmer/Applied Logistic Regression
4. Prognostic modelling with logistic regression analysis: a comparison of selection and estimation methods in small data sets. (Statistics in Medicine)
5. Propensity score estimation with boosted regression for evaluating causal effects in observational studies.
6. Clinical Prediction Rules
7. Boosting Algorithms: Regularization, Prediction and Model Fitting. Rejoinder.
8. The measurement of observer agreement for categorical data.
9. Misc Functions of the Department of Statistics (e1071), TU Wien
10. Predicting breast cancer survivability: a comparison of three data mining methods

Their papers

• Bootstrap Methods for Developing Predictive Models (2004) — 620 citations
• Automated variable selection methods for logistic regression produced unstable models for predicting acute myocardial infarction mortality. (2004) — 344 citations
• Using methods from the data mining and machine learning literature for disease classification and prediction: A case study examining classification of heart failure sub-types (2013) — 320 citations
• A population-based study of the drug interaction between proton pump inhibitors and clopidogrel (2009) — 789 citations
• Safety and Efficacy of Drug-Eluting and Bare Metal Stents: Comprehensive Meta-Analysis of Randomized Trials and Observational Studies (2009) — 594 citations
• Relation of Disease Pathogenesis and Risk Factors to Heart Failure With Preserved or Reduced Ejection Fraction: Insights From the Framingham Heart Study of the National Heart, Lung, and Blood Institute (2009) — 688 citations
• Relation between age and cardiovascular disease in men and women with diabetes compared with non-diabetic people: a population-based retrospective cohort study. (2006) — 684 citations
• Predicting mortality among patients hospitalized for heart failure: derivation and validation of a clinical model. (2003) — 1,372 citations
• Adherence with statin therapy in elderly patients with and without acute coronary syndromes. (2002) — 691 citations
• Advantages and disadvantages of using artificial neural networks versus logistic regression for predicting medical outcomes. (1996)