Andrew Beam

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Isaac S Kohane, Andrew L Beam, Kun-Hsing Yu, 2019, Artificial Intelligence and Machine Learning for Business for Non-Engineers.

Translating Artificial Intelligence Into Clinical Care.

I. Kohane, Andrew Beam, 2016, JAMA.

Optimization of Nonlinear Dose- and Concentration-Response Models Utilizing Evolutionary Computation

Andrew L Beam, Alison A Motsinger-Reif, Andrew Beam, 2011, Dose-response : a publication of International Hormesis Society.

Factors associated with clinical inertia in type 2 diabetes mellitus patients treated with metformin monotherapy

S. Shaw, Andrew Beam, Arnaub K Chatterjee, 2019, Current medical research and opinion.

Development of an Algorithm to Identify Patients with Physician-Documented Insomnia

Andrew L. Beam, Isaac S. Kohane, Uri Kartoun, 2018, Scientific Reports.

Challenges to the Reproducibility of Machine Learning Models in Health Care.

Marzyeh Ghassemi, Andrew L Beam, Arjun K Manrai, 2020, JAMA.

Deep learning predicts tuberculosis drug resistance status from genome sequencing data

I. Kohane, Andrew Beam, L. Freschi, 2018, bioRxiv.

Big Data and Machine Learning in Health Care.

I. Kohane, Andrew Beam, 2018, JAMA.

Beyond multidrug resistance: Leveraging rare variants with machine and statistical learning models in Mycobacterium tuberculosis resistance prediction

I. Kohane, Andrew Beam, L. Freschi, 2019, EBioMedicine.

Trends and Focus of Machine Learning Applications for Health Research

Brett K. Beaulieu-Jones, Samuel G. Finlayson, Adrian V. Dalca, 2019, JAMA network open.

ESICM LIVES 2016: part one

Hester F. Lingsma, A. M. Cavalheiro, H. S. King, 2016, Intensive Care Medicine Experimental.

Sharpening the Resolution on Data Matters: A Brief Roadmap for Understanding Deep Learning for Medical Data.

Andrew Beam, A. Schmaltz, 2020, The spine journal : official journal of the North American Spine Society.

Machine Learning in Clinical Journals: Moving From Inscrutable to Informative.

Andrew Beam, B. Nallamothu, Karandeep Singh, 2020, Circulation. Cardiovascular quality and outcomes.

Learning Contextual Hierarchical Structure of Medical Concepts with Poincairé Embeddings to Clarify Phenotypes

Andrew L. Beam, Isaac S. Kohane, Brett K. Beaulieu-Jones, 2018, PSB.

Opportunities in Machine Learning for Healthcare

R. Ranganath, M. Ghassemi, Peter F. Schulam, 2018, ArXiv.

Machine learning on drug-specific data to predict small molecule teratogenicity.

Andrew Beam, D. Aronoff, M. Shen, 2020, Reproductive toxicology.

Ex-Vivo Modeling for Heritability Assessment and Genetic Mapping in Pharmacogenomics.

Tammy M. Havener, Chad C. Brown, Andrew Beam, 2011, Proceedings. American Statistical Association. Annual Meeting.

Deep Learning Methods for Proximal Inference via Maximum Moment Restriction

J. Robins, Andrew Beam, Benjamin Kompa, 2022, ArXiv.

Effectiveness of 17-OHP for Prevention of Recurrent Preterm Birth: A Retrospective Cohort Study

S. Hernández-Díaz, Andrew Beam, Joe B Hakim, 2021, American Journal of Perinatology.

An investigation of gene-gene interactions in dose-response studies with Bayesian nonparametrics

Jon Doyle, Andrew L. Beam, Alison A. Motsinger-Reif, 2015, BioData Mining.

Deep Learning Methods for Proximal Inference via Maximum Moment Restriction

J. Robins, Andrew Beam, Benjamin Kompa, 2022, NeurIPS.

The Effect of Mastitis Upon Milk Production

Andrew Beam, A. Shaw, 1935 .

Bayesian Neural Networks for Genetic Association Studies of Complex Disease

Andrew Beam, A. Motsinger-Reif, Jon Doyle, 2014, 1404.3989.

Auditory Brainstem Response in Infants and Children with Autism: A Meta-Analysis

I. Kohane, Andrew Beam, O. Miron, 2017, 1710.03613.

Bayesian neural networks for detecting epistasis in genetic association studies

Jon Doyle, Andrew L. Beam, Alison A. Motsinger-Reif, 2014, BMC Bioinformatics.

Understanding the Genetic Etiology of Complex Phenotypes using Bayesian Neural Networks

Andrew Beam, 2014 .

Association of Sex With Recurrence of Autism Spectrum Disorder Among Siblings

Kathe P. Fox, S. Nelson, I. Kohane, 2017, JAMA pediatrics.

Time to reality check the promises of machine learning-powered precision medicine

Kellyn F Arnold, Marc de Kamps, Mark S. Gilthorpe, 2020, The Lancet. Digital health.

Adversarial attacks on medical machine learning

Andrew L. Beam, Isaac S. Kohane, Jonathan L. Zittrain, 2019, Science.

Statistical Physics for Medical Diagnostics: Learning, Inference, and Optimization Algorithms

Abolfazl Ramezanpour, Alireza Mashaghi, Andrew L Beam, 2020, Diagnostics.

Concordance between gene expression in peripheral whole blood and colonic tissue in children with inflammatory bowel disease

I. Kohane, S. Kong, Andrew Beam, 2019, PloS one.

Adversarial Attacks Against Medical Deep Learning Systems pdf

Andrew L. Beam, Isaac S. Kohane, Samuel G. Finlayson, 2018, ArXiv.

Utilization, Cost, and Outcome of Branded vs Compounded 17-Alpha Hydroxyprogesterone Caproate in Prevention of Preterm Birth

I. Kohane, Andrew Beam, N. Palmer, 2017, JAMA internal medicine.

Long term mortality in critically ill burn survivors.

Andrew Beam, A. Salim, K. Christopher, 2017, Burns : journal of the International Society for Burn Injuries.

Predictive Modeling of Physician-Patient Dynamics That Influence Sleep Medication Prescriptions and Clinical Decision-Making

I. Kohane, S. Shaw, Andrew Beam, 2017, Scientific Reports.

Machine learning for patient risk stratification: standing on, or looking over, the shoulders of clinicians?

I. Kohane, G. Weber, Andrew Beam, 2021, npj Digital Medicine.

Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence

L. Peng, G. Collins, B. van Calster, 2021, BMJ Open.

Medication Utilization in Children Born Preterm in the First Two Years of Life

Kathe P. Fox, K. Mandl, Andrew Beam, 2021, Journal of Perinatology.

Empirical Frequentist Coverage of Deep Learning Uncertainty Quantification Procedures

Jasper Snoek, Benjamin Kompa, Andrew Beam, 2020, Entropy.

Medical journals should embrace preprints to address the reproducibility crisis.

Luke Oakden-Rayner, Andrew L Beam, Lyle J Palmer, 2018, International journal of epidemiology.

Coarse-to-Fine Memory Matching for Joint Retrieval and Classification pdf

Allen Schmaltz, Andrew Beam, Andrew Beam, 2020, ArXiv.

The false hope of current approaches to explainable artificial intelligence in health care.

M. Ghassemi, Andrew Beam, L. Oakden-Rayner, 2021, The Lancet. Digital health.

Specificity of International Classification of Diseases codes for bronchopulmonary dysplasia: an investigation using electronic health record data and a large insurance database

Andrew Beam, R. Parad, Keith R Hirst, 2021, Journal of Perinatology.

Automated grouping of medical codes via multiview banded spectral clustering

Tianxi Cai, Zeling He, Yichi Zhang, 2019, J. Biomed. Informatics.

Practical guidance on artificial intelligence for health-care data.

Andrew L. Beam, Marzyeh Ghassemi, Peter Schulam, 2019, The Lancet. Digital health.

Fast Hamiltonian Monte Carlo Using GPU Computing

Jon Doyle, Andrew L. Beam, Sujit K. Ghosh, 2014, 1402.4089.

Clinical Concept Embeddings Learned from Massive Sources of Multimodal Medical Data

Tianxi Cai, Griffin M. Weber, Andrew L. Beam, 2018, PSB.

Artificial Intelligence in Medicine.

I. Kohane, J. Drazen, E. Rubin, 2023, The New England journal of medicine.

Clinical Concept Embeddings Learned from Massive Sources of Medical Data pdf

Tianxi Cai, Andrew L. Beam, Benjamin Kompa, 2018, ArXiv.

Machine Learning for Health (ML4H) Workshop at NeurIPS 2018 pdf

Irene Chen, Marzyeh Ghassemi, Alexandre Yahi, 2018, ArXiv.

Xenobiotic-Metabolizing Enzyme and Transporter Gene Expression in Primary Cultures of Human Hepatocytes Modulated by Toxcast Chemicals

David M. Reif, Richard S Judson, Andrew L Beam, 2010, Journal of toxicology and environmental health. Part B, Critical reviews.

Beyond IC50s: Towards Robust Statistical Methods for in vitro Association Studies

Andrew Beam, Alison Motsinger-Reif, Andrew Beam, 2014, Journal of pharmacogenomics & pharmacoproteomics.

Zebrafish developmental screening of the ToxCast™ Phase I chemical library.

David M. Reif, N Kleinstreuer, D J Dix, 2012, Reproductive toxicology.

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension

Cecilia S Lee, P. Keane, D. Moher, 2020, Nature Medicine.

Auditory brainstem response in infants and children with autism spectrum disorder: A meta‐analysis of wave V

I. Kohane, Andrew Beam, O. Miron, 2017, Autism research : official journal of the International Society for Autism Research.

Clinical Concept Embeddings Learned from Massive Sources of Medical Data

I. Kohane, T. Cai, Andrew Beam, 2018, ArXiv.

Adversarial attacks on medical machine learning

I. Kohane, Joichi Ito, Andrew Beam, 2019, Science.

Exemplar Auditing for Multi-Label Biomedical Text Classification pdf

Allen Schmaltz, Andrew Beam, Andrew Beam, 2020, ArXiv.