Raquel Dias

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 18 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 25 citations into it
• Molecular Biology — 24 citations into it
• Genetics — 15 citations into it
• Medical & Health AI — 11 citations into it
• Health Informatics — 10 citations into it
• Radiology, Nuclear Medicine and Imaging — 10 citations into it
• Computational Biology & Bioinformatics — 7 citations into it

Whom Raquel Dias trusts overall

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

1. Daniel Quang
2. Erik P. Garrison
3. Haiming Tang
4. Effy Vayena
5. Xiaohui S. Xie
6. Riccardo Miotto
7. Jingxue Wang
8. Andre Esteva
9. Ryan Poplin
10. Geoffrey E. Hinton

Papers from Raquel Dias's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Going deeper with convolutions
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklist (2020) — 485 citations
• Artificial intelligence in clinical and genomic diagnostics (2019) — 357 citations