Pierson, Emma

Mobility network models of COVID-19 explain inequities and inform reopening

Chang, S., Pierson, E., Koh, P. W., Gerardin, J., Redbird, B., Grusky, D., & Leskovec, J. (2021) · Nature

COVID-19 epidemiological studiesMathematical and Theoretical Epidemiology and Ecology Models

Cited by 1,533

Algorithmic Decision Making and the Cost of Fairness

Corbett-Davies, S., Pierson, E., Feller, A., Goel, S., & Huq, A. (2017) · Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Ethics and Social Impacts of AIArtificial Intelligence in Law

Cited by 1,149

Ethical Machine Learning in Healthcare

Chen, I. Y., Pierson, E., Rose, S., Joshi, S., Ferryman, K., & Ghassemi, M. (2021) · Annual Review of Biomedical Data Science

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 645

ZIFA: Dimensionality reduction for zero-inflated single-cell gene expression analysis

Pierson, E., & Yau, C. (2015) · Genome Biology

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 577

A large-scale analysis of racial disparities in police stops across the United States

Pierson, E., Simoiu, C., Overgoor, J., Corbett-Davies, S., Jenson, D., Shoemaker, A., Ramachandran, V., Barghouty, P., Phillips, C., Shroff, R., et al. (2020) · Nature Human Behaviour

Policing Practices and PerceptionsCriminal Justice and Corrections Analysis

Cited by 552

WILDS: A Benchmark of in-the-Wild Distribution Shifts

Koh, P. W., Sagawa, S., Marklund, H., Xie, S. M., Zhang, M., Balsubramani, A., Hu, W., Yasunaga, M., Phillips, R. L., Gao, I., et al. (2020) · arXiv

Domain Adaptation and Few-Shot LearningMachine Learning and Data Classification

Cited by 518

Concept Bottleneck Models

Koh, P. W., Nguyen, T., Tang, Y. S., Mussmann, S., Pierson, E., Kim, B., & Liang, P. (2020) · arXiv

Explainable Artificial Intelligence (XAI)Machine Learning in Healthcare

Cited by 338

An algorithmic approach to reducing unexplained pain disparities in underserved populations

Pierson, E., Cutler, D. M., Leskovec, J., Mullainathan, S., & Obermeyer, Z. (2021) · Nature Medicine

Artificial Intelligence in Healthcare and EducationArtificial Intelligence in Healthcare

Cited by 268

Sharing and Specificity of Co-expression Networks across 35 Human Tissues

Pierson, E., the GTEx Consortium, Koller, D., Battle, A., & Mostafavi, S. (2015) · PLOS Computational Biology

Bioinformatics and Genomic NetworksGene Regulatory Network Analysis

Cited by 177

Artificial Intelligence in Cardiovascular Care—Part 2: Applications

Jain, S. S., Elias, P., Poterucha, T., Randazzo, M., Lopez Jimenez, F., Khera, R., Perez, M., Ouyang, D., Pirruccello, J., Salerno, M., et al. (2024) · Journal of the American College of Cardiology

Artificial Intelligence in Healthcare and EducationArtificial Intelligence in Healthcare

Cited by 74

Predicting pregnancy using large-scale data from a women's health tracking mobile application

Liu, B., Shi, S., Wu, Y., Thomas, D., Symul, L., Pierson, E., & Leskovec, J. (2019) · The World Wide Web Conference

Artificial Intelligence in HealthcareMobile Health and mHealth Applications

Cited by 34

MediQ: Question-Asking LLMs and a Benchmark for Reliable Interactive Clinical Reasoning

Li, S., Balachandran, V., Feng, S., Ilgen, J., Pierson, E., Koh, P., & Tsvetkov, Y. (2024) · Advances in Neural Information Processing Systems 37

Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications

Cited by 19