Peter Szolovits

Artificial Intelligence · 1981–2024

A researcher in the Science corpus: 35 papers; trusts 235 researchers and is trusted by 62 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 307 citations into it; #6,364 of 35,345 by trust here, #2,652 by citations
• Molecular Biology — 219 citations into it; #4,439 of 17,773 by trust here, #7,980 by citations
• Natural Language Processing — 117 citations into it
• Genetics — 80 citations into it
• Computer Vision and Pattern Recognition — 72 citations into it; #11,090 of 21,575 by trust here, #2,712 by citations
• Evaluation & Benchmarks — 41 citations into it; #1,932 of 3,147 by trust here, #608 by citations
• Safety, Robustness & Interpretability — 40 citations into it; #725 of 2,251 by trust here, #849 by citations
• Statistics and Probability — 34 citations into it

Whom Peter Szolovits trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Sepp Hochreiter
5. Yann LeCun
6. Ilya Sutskever
7. Yuan Luo
8. Alex Krizhevsky
9. Tomas Mikolov
10. J. Urgen Schmidhuber

Who trusts Peter Szolovits overall

1. Yuan Luo
2. Zexian Zeng
3. Chao Yu
4. Yu Deng
5. Linyang Li
6. Trishan Panch
7. Silvio Amir
8. Adyasha Maharana
9. Siddhant Garg
10. Liang Yao

Papers from Peter Szolovits's perspective

Ordered by how strongly the researchers Peter Szolovits 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. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• MIMIC-III, a freely accessible critical care database (2016) — 8,772 citations
• Can AI Help Reduce Disparities in General Medical and Mental Health Care? (2019) — 373 citations
• What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams (2020) — 1,893 citations
• Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment (2019) — 1,382 citations
• Clinically Accurate Chest X-Ray Report Generation (2019) — 353 citations
• Continuous State-Space Models for Optimal Sepsis Treatment: a Deep Reinforcement Learning Approach (2017) — 238 citations
• De-identification of patient notes with recurrent neural networks (2016) — 433 citations
• A Multivariate Timeseries Modeling Approach to Severity of Illness Assessment and Forecasting in ICU with Sparse, Heterogeneous Clinical Data (2015) — 238 citations
• Automatic lymphoma classification with sentence subgraph mining from pathology reports. (2014) — 58 citations
• Toward high-throughput phenotyping: unbiased automated feature extraction and selection from knowledge sources (2015) — 162 citations
• Bridging semantics and syntax with graph algorithms - state-of-the-art of extracting biomedical relations (2017) — 75 citations
• Supplementary Issue: Computational Advances in Cancer Informatics (a) — 103 citations
• Segment convolutional neural networks (Seg-CNNs) for classifying relations in clinical notes (2018) — 69 citations
• Development of phenotype algorithms using electronic medical records and incorporating natural language processing (2015) — 269 citations
• 3D-MICE: integration of cross-sectional and longitudinal imputation for multi-analyte longitudinal clinical data (2017) — 97 citations
• Assessing the potential of GPT-4 to perpetuate racial and gender biases in health care: a model evaluation study. (2024) — 430 citations
• Knowledge representation (2019)
• Is BERT Really Robust? Natural Language Attack on Text Classification and Entailment (2019)
• Artificial intelligence, machine learning and health systems (2018) — 460 citations
• Deep Reinforcement Learning for Sepsis Treatment (2017) — 200 citations