Nayha Dixit

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Nayha Dixit trusts overall

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

  1. R. Caruana

Papers from Nayha Dixit's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Mastering the game of Go with deep neural networks and tree search
  3. Radiomics: Extracting more information from medical images using advanced feature analysis (European Journal of Cancer)
  4. An empirical comparison of supervised learning algorithms
  5. Machine Learning methods for Quantitative Radiomic Biomarkers (Scientific Reports)
  6. Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.
  7. Intelligible Models for HealthCare: Predicting Pneumonia Risk and Hospital 30-day Readmission
  8. Do we need hundreds of classifiers to solve real world classification problems?
  9. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach (Nature Communications)
  10. Deep Reinforcement Learning for Automated Radiation Adaptation in Lung Cancer

Their papers