How machine-learning recommendations influence clinician treatment selections: the example of antidepressant selection von Jacobs, Maia, Pradier, Melanie F., McCoy, Thomas H., Perlis, Roy H., Doshi-Velez, Finale, Gajos, Krzysztof Z.

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Assessing topic model relevance: Evaluation and informative priors von Fan, Angela, Doshi‐Velez, Finale, Miratrix, Luke

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Comorbidity clusters in autism spectrum disorders: an electronic health record time-series analysis von Doshi-Velez, Finale, Ge, Yaorong, Kohane, Isaac

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Machine Learning Techniques for Accountability von Kim, Been, Doshi‐Velez, Finale

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Bayesian Nonparametric Methods for Partially-Observable Reinforcement Learning von Doshi-Velez, Finale, Pfau, David, Wood, Frank, Roy, Nicholas

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Predicting change in diagnosis from major depression to bipolar disorder after antidepressant initiation von Pradier, Melanie F, Hughes, Michael C, McCoy, Jr, Thomas H, Barroilhet, Sergio A, Doshi-Velez, Finale, Perlis, Roy H

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Depth-Bounded Statistical PCFG Induction as a Model of Human Grammar Acquisition von Jin, Lifeng, Schwartz, Lane, Doshi-Velez, Finale, Miller, Timothy, Schuler, William

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Designing Reinforcement Learning Algorithms for Digital Interventions: Pre-Implementation Guidelines von Trella, Anna L, Zhang, Kelly W, Nahum-Shani, Inbal, Shetty, Vivek, Doshi-Velez, Finale, Murphy, Susan A

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Predicting treatment dropout after antidepressant initiation von Pradier, Melanie F., McCoy Jr, Thomas H., Hughes, Michael, Perlis, Roy H., Doshi-Velez, Finale

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Improving counterfactual reasoning with kernelised dynamic mixing models von Parbhoo, Sonali, Gottesman, Omer, Ross, Andrew Slavin, Komorowski, Matthieu, Faisal, Aldo, Bon, Isabella, Roth, Volker, Doshi-Velez, Finale

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Electronic Health Record Based Algorithm to Identify Patients with Autism Spectrum Disorder von Lingren, Todd, Chen, Pei, Bochenek, Joseph, Doshi-Velez, Finale, Manning-Courtney, Patty, Bickel, Julie, Wildenger Welchons, Leah, Reinhold, Judy, Bing, Nicole, Ni, Yizhao, Barbaresi, William, Mentch, Frank, Basford, Melissa, Denny, Joshua, Vazquez, Lyam, Perry, Cassandra, Namjou, Bahram, Qiu, Haijun, Connolly, John, Abrams, Debra, Holm, Ingrid A, Cobb, Beth A, Lingren, Nataline, Solti, Imre, Hakonarson, Hakon, Kohane, Isaac S, Harley, John, Savova, Guergana

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Association between prescriber practices and major depression treatment outcomes von Rathnam, Sarah, Sharma, Abhishek, Hart, Kamber L., Verhaak, Pilar F., McCoy, Thomas H., Perlis, Roy H., Doshi-Velez, Finale

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Generalization in Clinical Prediction Models: The Blessing and Curse of Measurement Indicator Variables von Futoma, Joseph, Simons, Morgan, Doshi-Velez, Finale, Kamaleswaran, Rishikesan

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An interpretable RL framework for pre-deployment modeling in ICU hypotension management von Zhang, Kristine, Wang, Henry, Du, Jianzhun, Chu, Brian, Arévalo, Aldo Robles, Kindle, Ryan, Celi, Leo Anthony, Doshi-Velez, Finale

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Unsupervised Grammar Induction with Depth-bounded PCFG von Jin, Lifeng, Doshi-Velez, Finale, Miller, Timothy, Schuler, William, Schwartz, Lane

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Guidelines for reinforcement learning in healthcare von Gottesman, Omer, Johansson, Fredrik, Komorowski, Matthieu, Faisal, Aldo, Sontag, David, Doshi-Velez, Finale, Celi, Leo Anthony

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The myth of generalisability in clinical research and machine learning in health care von Futoma, Joseph, Simons, Morgan, Panch, Trishan, Doshi-Velez, Finale, Celi, Leo Anthony

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Summarizing agent strategies von Amir, Ofra, Doshi-Velez, Finale, Sarne, David

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Do no harm: a roadmap for responsible machine learning for health care von Wiens, Jenna, Saria, Suchi, Sendak, Mark, Ghassemi, Marzyeh, Liu, Vincent X., Doshi-Velez, Finale, Jung, Kenneth, Heller, Katherine, Kale, David, Saeed, Mohammed, Ossorio, Pilar N., Thadaney-Israni, Sonoo, Goldenberg, Anna

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Evaluating Machine Learning Articles von Doshi-Velez, Finale, Perlis, Roy H

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