Saima Sadiq

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Saima Sadiq trusts overall

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

  1. Jerome H. Friedman
  2. Yoav Freund
  3. Bernhard Schölkopf
  4. Trevor J. Hastie
  5. V. Ramalingam

Papers from Saima Sadiq's perspective

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

  1. Greedy function approximation: A gradient boosting machine.
  2. Random Forests
  3. Effective diagnosis of heart disease through neural networks ensembles (Expert systems with applications)
  4. A Short Introduction to Boosting
  5. Incorporating Invariances in Support Vector Learning Machines
  6. A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty-Three Old and New Classification Algorithms
  7. Computer aided decision making for heart disease detection using hybrid neural network-Genetic algorithm (Comput. Methods Programs Biomed.)
  8. Deep learning approach for active classification of electrocardiogram signals (Information Sciences)
  9. Can machine-learning improve cardiovascular risk prediction using routine clinical data? (PLoS ONE)
  10. Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine (Database J. Biol. Databases Curation)

Their papers