Andrew L. Beam

21 papers Misc 2Journal 18Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Development and validation of a deep learning model for diagnosing neuropathic corneal pain via in vivo confocal microscopy. npj Digit. Medicine Neslihan Dilruba Koseoglu, Eric Chen, Rudraksh Tuwani, Benjamin Kompa, Stephanie M. Cox, M. Cuneyt Ozmen, Mina Massaro-Giordano, Andrew L. Beam, Pedram Hamrah
2025	J	`jnl`	Doubly Robust Monte Carlo Tree Search. CoRR Manqing Liu, Andrew L. Beam
2024	J	`jnl`	DAG-aware Transformer for Causal Effect Estimation. CoRR Manqing Liu, David R. Bellamy, Andrew L. Beam
2022	J	`jnl`	Deep Learning Methods for Proximal Inference via Maximum Moment Restriction. CoRR Benjamin Kompa, David R. Bellamy, Thomas Kolokotrones, James M. Robins, Andrew L. Beam
2022	—	`conf`	MedSelect: Selective Labeling for Medical Image Classification Using Meta-Learning. MIDL Damir Vrabac, Akshay Smit, Yujie He, Andrew Y. Ng, Andrew L. Beam, Pranav Rajpurkar
2022	J	`jnl`	Self-Supervision on Images and Text Reduces Reliance on Visual Shortcut Features. CoRR Anil Palepu, Andrew L. Beam
2022	J	`jnl`	TIER: Text-Image Entropy Regularization for CLIP-style models. CoRR Anil Palepu, Andrew L. Beam
2021	J	`jnl`	Empirical Frequentist Coverage of Deep Learning Uncertainty Quantification Procedures. Entropy Benjamin Kompa, Jasper Snoek, Andrew L. Beam
2021	J	`jnl`	Machine learning for patient risk stratification: standing on, or looking over, the shoulders of clinicians? npj Digit. Medicine Brett K. Beaulieu-Jones, William Yuan, Gabriel A. Brat, Andrew L. Beam, Griffin M. Weber, Marshall Ruffin, Isaac S. Kohane
2021	J	`jnl`	MedSelect: Selective Labeling for Medical Image Classification Combining Meta-Learning with Deep Reinforcement Learning. CoRR Akshay Smit, Damir Vrabac, Yujie He, Andrew Y. Ng, Andrew L. Beam, Pranav Rajpurkar
2021	J	`jnl`	Second opinion needed: communicating uncertainty in medical machine learning. npj Digit. Medicine Benjamin Kompa, Jasper Snoek, Andrew L. Beam
2020	Misc	`conf`	Clinical Concept Embeddings Learned from Massive Sources of Multimodal Medical Data. PSB Andrew L. Beam, Benjamin Kompa, Allen Schmaltz, Inbar Fried, Griffin M. Weber, Nathan P. Palmer, Xu Shi, Tianxi Cai, Isaac S. Kohane
2020	J	`jnl`	Evaluating Progress on Machine Learning for Longitudinal Electronic Healthcare Data. CoRR David R. Bellamy, Leo A. Celi, Andrew L. Beam
2019	Misc	`conf`	Learning Contextual Hierarchical Structure of Medical Concepts with Poincairé Embeddings to Clarify Phenotypes. PSB Brett K. Beaulieu-Jones, Isaac S. Kohane, Andrew L. Beam
2018	J	`jnl`	Adversarial Attacks Against Medical Deep Learning Systems. CoRR Samuel G. Finlayson, Isaac S. Kohane, Andrew L. Beam
2018	J	`jnl`	Clinical Concept Embeddings Learned from Massive Sources of Medical Data. CoRR Andrew L. Beam, Benjamin Kompa, Inbar Fried, Nathan P. Palmer, Xu Shi, Tianxi Cai, Isaac S. Kohane
2018	J	`jnl`	Learning Contextual Hierarchical Structure of Medical Concepts with Poincairé Embeddings to Clarify Phenotypes. CoRR Brett K. Beaulieu-Jones, Isaac S. Kohane, Andrew L. Beam
2018	J	`jnl`	Machine Learning for Health (ML4H) Workshop at NeurIPS 2018. CoRR Natalia Antropova, Andrew L. Beam, Brett K. Beaulieu-Jones, Irene Chen, Corey Chivers, Adrian V. Dalca, Samuel G. Finlayson, Madalina Fiterau, Jason Alan Fries, Marzyeh Ghassemi, Mike Hughes, Bruno Jedynak, Jasvinder S. Kandola, Matthew B. A. McDermott, Tristan Naumann, Peter Schulam, Farah Shamout, Alexandre Yahi
2018	J	`jnl`	Opportunities in Machine Learning for Healthcare. CoRR Marzyeh Ghassemi, Tristan Naumann, Peter Schulam, Andrew L. Beam, Rajesh Ranganath
2015	J	`jnl`	An investigation of gene-gene interactions in dose-response studies with Bayesian nonparametrics. BioData Min. Andrew L. Beam, Alison A. Motsinger-Reif, Jon Doyle
2014	J	`jnl`	Bayesian neural networks for detecting epistasis in genetic association studies. BMC Bioinform. Andrew L. Beam, Alison A. Motsinger-Reif, Jon Doyle