Marzyeh Ghassemi

Artificial Intelligence · 2014–2025

A researcher in the Science corpus: 34 papers; trusts 670 researchers and is trusted by 57 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 479 citations into it; #12,285 of 35,345 by trust here, #4,747 by citations
• Computer Vision and Pattern Recognition — 206 citations into it; #10,660 of 21,575 by trust here, #2,792 by citations
• Radiology, Nuclear Medicine and Imaging — 116 citations into it
• Safety, Robustness & Interpretability — 108 citations into it
• Health Informatics — 103 citations into it; #44 of 240 by trust here, #14 by citations
• Representation & Self-Supervised Learning — 102 citations into it; #2,608 of 3,145 by trust here, #2,957 by citations
• Natural Language Processing — 96 citations into it
• Evaluation & Benchmarks — 81 citations into it; #1,914 of 3,147 by trust here, #584 by citations

Whom Marzyeh Ghassemi trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Diederik P. Kingma
4. Alex Krizhevsky
5. Mohammed Saeed
6. Yann LeCun
7. Kaiming He
8. Ilya Sutskever
9. Radford M. Neal
10. Andrew Y. Ng

Who trusts Marzyeh Ghassemi overall

1. Chao Yu
2. Shamim Nemati
3. Li-Fang Cheng
4. Jiming Liu
5. Alistair E. W. Johnson
6. Irene Y. Chen
7. Joseph D. Futoma
8. Adnan Qayyum
9. Hossein Soleimani
10. Pierre Humbert

Papers from Marzyeh Ghassemi's perspective

Ordered by how strongly the researchers Marzyeh Ghassemi 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. 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. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

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
• Clinically Accurate Chest X-Ray Report Generation (2019) — 353 citations
• SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness (2020) — 155 citations
• Continuous State-Space Models for Optimal Sepsis Treatment: a Deep Reinforcement Learning Approach (2017) — 238 citations
• Challenges to the Reproducibility of Machine Learning Models in Health Care (2020) — 338 citations
• Ethical Machine Learning in Healthcare (2020) — 577 citations
• Optimal medication dosing from suboptimal clinical examples: A deep reinforcement learning approach (2016) — 198 citations
• A Multivariate Timeseries Modeling Approach to Severity of Illness Assessment and Forecasting in ICU with Sparse, Heterogeneous Clinical Data (2015) — 238 citations
• A data-driven approach to optimized medication dosing: a focus on heparin (2014) — 65 citations
• Self-Supervised Contrastive Learning of Protein Representations By Mutual Information Maximization (2020) — 93 citations
• Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations (2021) — 830 citations
• TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods (2024) — 2,500 citations
• PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods (2025) — 435 citations
• FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare (2023) — 491 citations
• Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors (2022) — 315 citations
• AI recognition of patient race in medical imaging: a modelling study (2021) — 504 citations
• Do as AI say: susceptibility in deployment of clinical decision-aids (2021) — 431 citations
• Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning (2021) — 25 citations
• The false hope of current approaches to explainable artificial intelligence in health care. (2021) — 1,184 citations