Xiangchun Li

Artificial Intelligence · 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 Xiangchun Li trusts overall

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

  1. Cynthia Rudin

Papers from Xiangchun Li's perspective

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

  1. Deep Learning
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. ImageNet classification with deep convolutional neural networks
  4. Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead
  5. Assessment of algorithms for mitosis detection in breast cancer histopathology images (Medical Image Anal.)
  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. Classification of breast cancer histology images using Convolutional Neural Networks (PLoS ONE)
  9. Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer (Nature Medicine)
  10. Opportunities and obstacles for deep learning in biology and medicine

Their papers