2019 (7)
Learning Contextual Hierarchical Structure of Medical Concepts with Poincairé Embeddings to Clarify Phenotypes. Beaulieu-Jones, B. K; Kohane, I. S; and Beam, A. L In PSB, pages 8–17, 2019.
Learning Contextual Hierarchical Structure of Medical Concepts with Poincairé Embeddings to Clarify Phenotypes. [link] paper   bibtex   abstract
Feature extraction for phenotyping from semantic and knowledge resources. Ning, W.; Chan, S.; Beam, A.; Yu, M.; Geva, A.; Liao, K.; Mullen, M.; Mandl, K. D; Kohane, I.; Cai, T.; and others Journal of biomedical informatics, 91: 103122. 2019.
Feature extraction for phenotyping from semantic and knowledge resources [link] paper   bibtex   abstract
Adversarial attacks on medical machine learning. Finlayson, S. G; Bowers, J. D; Ito, J.; Zittrain, J. L; Beam*, A. L; and Kohane*, I. S Science, 363(6433): 1287–1289. 2019.
Adversarial attacks on medical machine learning [link] paper   bibtex   abstract
Clinical Concept Embeddings Learned from Massive Sources of Multimodal Medical Data. Beam*, A. L; Kompa*, B.; Fried, I.; Palmer, N. P; Shi, X.; Cai, T.; and Kohane, I. S arXiv preprint arXiv:1804.01486. 2019.
Clinical Concept Embeddings Learned from Massive Sources of Multimodal Medical Data [link] paper   bibtex   abstract
Beyond multidrug resistance: Leveraging rare variants with machine and statistical learning models in Mycobacterium tuberculosis resistance prediction. Chen, M. L; Doddi, A.; Royer, J.; Freschi, L.; Schito, M.; Ezewudo, M.; Kohane, I. S; Beam*, A.; and Farhat*, M. EBioMedicine. 2019.
Beyond multidrug resistance: Leveraging rare variants with machine and statistical learning models in Mycobacterium tuberculosis resistance prediction [link] paper   bibtex   abstract
Practical guidance on artificial intelligence for health-care data. Ghassemi, M.; Naumann, T.; Schulam, P.; Beam, A. L; Chen, I. Y; and Ranganath, R. The Lancet Digital Health, 1(4): e157–e159. 2019.
Practical guidance on artificial intelligence for health-care data [link] paper   bibtex   abstract
Factors associated with clinical inertia in type 2 diabetes mellitus patients treated with metformin monotherapy. Kartoun, U.; Iglay, K.; Shankar, R R.; Beam, A.; Radican, L.; Chatterjee, A.; Pai, J. K; and Shaw, S. Current medical research and opinion, (just-accepted): 1–1. 2019.
Factors associated with clinical inertia in type 2 diabetes mellitus patients treated with metformin monotherapy [link] paper   bibtex   abstract
  2018 (8)
Postsurgical prescriptions for opioid naive patients and association with overdose and misuse: retrospective cohort study. Brat, G. A; Agniel, D.; Beam, A.; Yorkgitis, B.; Bicket, M.; Homer, M.; Fox, K. P; Knecht, D. B; McMahill-Walraven, C. N; Palmer, N.; and others Bmj, 360: j5790. 2018.
Postsurgical prescriptions for opioid naive patients and association with overdose and misuse: retrospective cohort study [link] paper   bibtex   abstract
Big data and machine learning in health care. Beam, A. L; and Kohane, I. S Jama, 319(13): 1317–1318. 2018.
Big data and machine learning in health care [pdf] paper   bibtex   abstract
Adversarial attacks against medical deep learning systems. Finlayson, S. G; Chung, H. W.; Kohane, I. S; and Beam, A. L arXiv preprint arXiv:1804.05296. 2018.
Adversarial attacks against medical deep learning systems [link] paper   bibtex   abstract
Development of an algorithm to identify patients with physician-documented insomnia. Kartoun, U.; Aggarwal, R.; Beam, A. L; Pai, J. K; Chatterjee, A. K; Fitzgerald, T. P; Kohane, I. S; and Shaw, S. Y Scientific reports, 8(1): 7862. 2018.
Development of an algorithm to identify patients with physician-documented insomnia [link] paper   bibtex   abstract
Opportunities in machine learning for healthcare. Ghassemi, M.; Naumann, T.; Schulam, P.; Beam, A. L; and Ranganath, R. arXiv preprint arXiv:1806.00388. 2018.
Opportunities in machine learning for healthcare [link] paper   bibtex   abstract
Medical journals should embrace preprints to address the reproducibility crisis. Oakden-Rayner, L.; Beam, A. L; and Palmer, L. J 2018.
Medical journals should embrace preprints to address the reproducibility crisis [link] paper   bibtex   abstract
Artificial intelligence in healthcare. Yu, K.; Beam, A. L; and Kohane, I. S Nature biomedical engineering, 2(10): 719. 2018.
Artificial intelligence in healthcare [link] paper   bibtex   abstract
Machine Learning for Health (ML4H) Workshop at NeurIPS 2018. Antropova, N.; Beam, A.; Beaulieu-Jones, B. K; Chen, I.; Chivers, C.; Dalca, A.; Finlayson, S.; Fiterau, M.; Fries, J. A.; Ghassemi, M.; and others arXiv preprint arXiv:1811.07216. 2018.
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  2017 (6)
Predictive modeling of physician-patient dynamics that influence sleep medication prescriptions and clinical decision-making. Beam*, A. L; Kartoun*, U.; Pai, J. K; Chatterjee, A. K; Fitzgerald, T. P; Shaw, S. Y; and Kohane, I. S Scientific reports, 7: 42282. 2017.
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Long term mortality in critically ill burn survivors. Nitzschke, S.; Offodile, A.; Cauley, R.; Frankel, J.; Beam, A.; Elias, K.; Gibbons, F.; Salim, A.; and Christopher, K. Burns. 2017.
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Association of sex with recurrence of autism spectrum disorder among siblings. Palmer, N.; Beam, A.; Agniel, D.; Eran, A.; Manrai, A.; Spettell, C.; Steinberg, G.; Mandl, K.; Fox, K.; Nelson, S. F; and others JAMA pediatrics, 171(11): 1107–1112. 2017.
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Utilization, cost, and outcome of branded vs compounded 17-alpha hydroxyprogesterone caproate in prevention of preterm birth. Fried*, I.; Beam*, A. L; Kohane, I. S; and Palmer, N. P JAMA internal medicine, 177(11): 1689–1690. 2017.
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Post-surgical opioid prescription duration and the association with overdose and abuse. Brat, G.; Agniel, D.; Beam, A.; Yorkgitis, B.; Bicket, M. C; Fox, K. P; Knecht, D.; Walraven, C.; Palmer, N.; and Kohane, I. S Journal of the American College of Surgeons, 225(4): e29. 2017.
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Auditory brainstem response in infants and children with autism spectrum disorder: A meta-analysis of wave V. Miron, O; Beam, A.; and Kohane, I. Autism research: official journal of the International Society for Autism Research. 2017.
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  2016 (2)
Fast hamiltonian monte carlo using gpu computing. Beam, A. L; Ghosh, S. K; and Doyle, J. Journal of Computational and Graphical Statistics, 25(2): 536–548. 2016.
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Translating artificial intelligence into clinical care. Beam, A. L; and Kohane, I. S Jama, 316(22): 2368–2369. 2016.
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  2015 (1)
An investigation of gene-gene interactions in dose-response studies with Bayesian nonparametrics. Beam, A. L; Motsinger-Reif, A. A; and Doyle, J. BioData mining, 8(1): 6. 2015.
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  2014 (2)
Understanding the Genetic Etiology of Complex Phenotypes using Bayesian Neural Networks. Beam, A. L.; and others . 2014.
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Bayesian neural networks for detecting epistasis in genetic association studies. Beam, A. L; Motsinger-Reif, A.; and Doyle, J. BMC bioinformatics, 15(1): 368. 2014.
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  2013 (1)
Beyond IC50s: Towards Robust Statistical Methods for in vitro Association Studies. Beam, A; and Motsinger-Reif, A 2013.
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  2012 (2)
Zebrafish developmental screening of the ToxCast™ Phase I chemical library. Padilla, S; Corum, D; Padnos, B; Hunter, D.; Beam, A; Houck, K.; Sipes, N; Kleinstreuer, N; Knudsen, T; Dix, D.; and others Reproductive toxicology, 33(2): 174–187. 2012.
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The Second Phase of ToxCast and Initial Applications to Chemical Prioritization. Dix, D.; Houck, K.; Judson, R.; Knudsen, T.; Little, S.; Martin, M.; Mortensen, H.; Reif, D.; Richard, A.; Setzer, W.; and others . 2012.
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  2011 (3)
Optimization of nonlinear dose-and concentration-response models utilizing evolutionary computation. Beam, A. L; and Motsinger-Reif, A. A Dose-Response, 9(3): dose–response. 2011.
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A Bayesian Framework for the Analysis of the Peroxisome Proliferator-Activated Receptor Signaling Pathway. Beam, A. . 2011.
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Ex-vivo modeling for heritability assessment and genetic mapping in pharmacogenomics. Motsinger-Reif, A.; Brown, C.; Havener, T.; Hardison, N.; Peters, E.; Beam, A.; Everrit, L.; and McLeod, H. In Proceedings. American Statistical Association. Annual Meeting, volume 2011, pages 306, 2011. NIH Public Access
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  2010 (1)
Xenobiotic-metabolizing enzyme and transporter gene expression in primary cultures of human hepatocytes modulated by ToxCast chemicals. Rotroff, D. M; Beam, A. L; Dix, D. J; Farmer, A.; Freeman, K. M; Houck, K. A; Judson, R. S; LeCluyse, E. L; Martin, M. T; Reif, D. M; and others Journal of Toxicology and Environmental Health, Part B, 13(2-4): 329–346. 2010.
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