Meng Yang

Artificial Intelligence · with Wang · 2018–2020

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

Subfields

Whom Meng Yang trusts overall

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

  1. Cynthia Rudin
  2. Anant Madabhushi
  3. M. Veta

Papers from Meng Yang's perspective

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

  1. Deep Learning
  2. Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead
  3. Assessment of algorithms for mitosis detection in breast cancer histopathology images (Medical Image Anal.)
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. ImageNet classification with deep convolutional neural networks
  6. Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: A cross-sectional study
  7. Image analysis and machine learning in digital pathology: Challenges and opportunities (Medical Image Anal.)
  8. Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer (Nature Medicine)
  9. Classification of breast cancer histology images using Convolutional Neural Networks (PLoS ONE)
  10. Opportunities and obstacles for deep learning in biology and medicine

Their papers