Jie Ma

Artificial Intelligence · with Collins · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jie Ma trusts overall

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

  1. Anne-Laure Boulesteix
  2. Ewout W. Steyerberg
  3. M. Pepe
  4. James Franklin
  5. David J. Hand
  6. Igor Kononenko
  7. Karel G. M. Moons
  8. Gary S. Collins
  9. Peter C. Austin
  10. B. Van calster

Papers from Jie Ma's perspective

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

  1. Do we need hundreds of classifiers to solve real world classification problems?
  2. A Plea for Neutral Comparison Studies in Computational Sciences
  3. Ten Simple Rules for Reducing Overoptimistic Reporting in Methodological Computational Research
  4. Internal validation of predictive models: efficiency of some procedures for logistic regression analysis. (Journal of Clinical Epidemiology)
  5. The elements of statistical learning: data mining, inference and prediction
  6. Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View
  7. Modern modelling techniques are data hungry: a simulation study for predicting dichotomous endpoints (BMC Medical Research Methodology)
  8. Classifier Technology and the Illusion of Progress
  9. The elements of statistical learning: data mining, inference, and prediction, 2nd Edition
  10. The Statistical Evaluation of Medical Tests for Classification and Prediction

Their papers