David F. Steiner

Artificial Intelligence · 2018–2022

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

Subfields

• Artificial Intelligence — 31 citations into it; #34,758 of 35,345 by trust here, #14,181 by citations
• Radiology, Nuclear Medicine and Imaging — 12 citations into it; #3,153 of 3,265 by trust here, #2,321 by citations

Whom David F. Steiner trusts overall

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

1. Maryellen Lissak Giger

Who trusts David F. Steiner overall

1. Eric J. Topol
2. Yahui Jiang

Papers from David F. Steiner's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Going deeper with convolutions
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. ImageNet Large Scale Visual Recognition Challenge
9. ImageNet: A large-scale hierarchical image database
10. Visualizing Higher-Layer Features of a Deep Network

Their papers

• "Hello AI": Uncovering the Onboarding Needs of Medical Practitioners for Human-AI Collaborative Decision-Making (2019) — 558 citations
• Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge (2022) — 592 citations
• Impact of Deep Learning Assistance on the Histopathologic Review of Lymph Nodes for Metastatic Breast Cancer (2018) — 410 citations