Shalmali Joshi

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Melissa McCraddenAustralian Institute for Machine learningEmail yang diverifikasi di adelaide.edu.au
Dr. Marzyeh GhassemiAssociate Professor, EECS/IMES, MITEmail yang diverifikasi di mit.edu
Anna GoldenbergScientist, SickKids Research Institute; Assistant Professor Department of Computer Science, University of TorontoEmail yang diverifikasi di utoronto.ca
Irene Y. ChenAssistant Professor, UC Berkeley and UC San FranciscoEmail yang diverifikasi di berkeley.edu
Sana TonekaboniBroad Institute of MIT and HarvardEmail yang diverifikasi di broadinstitute.org
Joydeep Ghosh(Chaired) Professor, ECE Dept., Univ. Texas at Austin; Faculty Dell Med, UT-Comp. Sc., McCombsEmail yang diverifikasi di utexas.edu
Sanmi KoyejoAssistant Professor, Stanford UniversityEmail yang diverifikasi di stanford.edu
Emma PiersonUniversity of California, BerkeleyEmail yang diverifikasi di berkeley.edu
Haoran ZhangPhD Student, Massachusetts Institute of TechnologyEmail yang diverifikasi di mit.edu
Been KimGoogle DeepMindEmail yang diverifikasi di csail.mit.edu
Finale Doshi-VelezProfessor, HarvardEmail yang diverifikasi di seas.harvard.edu
David DuvenaudAssociate Professor, University of TorontoEmail yang diverifikasi di cs.toronto.edu
Rajesh RanganathAssistant Professor, NYUEmail yang diverifikasi di cs.princeton.edu
Randi Zlotnik ShaulDirector Bioethics Department, The Hospital for Sick ChildrenEmail yang diverifikasi di sickkids.ca
Kieran R CampbellTorontoEmail yang diverifikasi di lunenfeld.ca
Frank RudziczDalhousie University, Computer Science ; Vector Institute for Artificial IntelligenceEmail yang diverifikasi di dal.ca
Quaid MorrisComputational and Systems Biology Program, Memorial Sloan Kettering Cancer CenterEmail yang diverifikasi di mskcc.org
Taylor W. KillianGraduate Researcher, University of TorontoEmail yang diverifikasi di cs.toronto.edu
David SontagProfessor, Massachusetts Institute of TechnologyEmail yang diverifikasi di csail.mit.edu
Suriya GunasekarMSR RedmondEmail yang diverifikasi di ttic.edu

Ikuti

Shalmali Joshi

Columbia University

Email yang diverifikasi di cumc.columbia.edu - Beranda

Machine Learning Healthcare


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
What clinicians want: contextualizing explainable machine learning for clinical end use S Tonekaboni, S Joshi, MD McCradden, A Goldenberg Machine learning for healthcare conference, 359-380, 2019	556	2019
Ethical machine learning in healthcare IY Chen, E Pierson, S Rose, S Joshi, K Ferryman, M Ghassemi Annual review of biomedical data science 4 (1), 123-144, 2021	514	2021
Ethical limitations of algorithmic fairness solutions in health care machine learning MD McCradden, S Joshi, M Mazwi, JA Anderson The Lancet Digital Health 2 (5), e221-e223, 2020	213	2020
Towards realistic individual recourse and actionable explanations in black-box decision making systems S Joshi, O Koyejo, W Vijitbenjaronk, B Kim, J Ghosh arXiv preprint arXiv:1907.09615, 2019	206	2019
Treating health disparities with artificial intelligence IY Chen, S Joshi, M Ghassemi Nature medicine 26 (1), 16-17, 2020	130	2020
Towards robust and reliable algorithmic recourse S Upadhyay, S Joshi, H Lakkaraju Advances in Neural Information Processing Systems 34, 16926-16937, 2021	120	2021
Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning MD McCradden, S Joshi, JA Anderson, M Mazwi, A Goldenberg, ... Journal of the American Medical Informatics Association 27 (12), 2024-2027, 2020	99	2020
What went wrong and when? Instance-wise feature importance for time-series black-box models S Tonekaboni, S Joshi, K Campbell, DK Duvenaud, A Goldenberg Advances in Neural Information Processing Systems 33, 799-809, 2020	91	2020
Exploring counterfactual explanations through the lens of adversarial examples: A theoretical and empirical analysis M Pawelczyk, C Agarwal, S Joshi, S Upadhyay, H Lakkaraju International Conference on Artificial Intelligence and Statistics, 4574-4594, 2022	80*	2022
Probabilistic machine learning for healthcare IY Chen, S Joshi, M Ghassemi, R Ranganath Annual review of biomedical data science 4 (1), 393-415, 2021	79	2021
An empirical framework for domain generalization in clinical settings H Zhang, N Dullerud, L Seyyed-Kalantari, Q Morris, S Joshi, M Ghassemi Proceedings of the conference on health, inference, and learning, 279-290, 2021	71	2021
Can you fake it until you make it? impacts of differentially private synthetic data on downstream classification fairness V Cheng, VM Suriyakumar, N Dullerud, S Joshi, M Ghassemi Proceedings of the 2021 ACM Conference on Fairness, Accountability, and …, 2021	64	2021
xGEMs: Generating Examplars to Explain Black-Box Models S Joshi, O Koyejo, B Kim, J Ghosh https://arxiv.org/abs/1806.08867, 2018	50	2018
Making machine learning matter to clinicians: model actionability in medical decision-making DE Ehrmann, S Joshi, SD Goodfellow, ML Mazwi, D Eytan NPJ Digital Medicine 6 (1), 7, 2023	31	2023
Identifiable phenotyping using constrained non-negative matrix factorization S Joshi, S Gunasekar, D Sontag, G Joydeep Machine Learning for Healthcare Conference, 17-41, 2016	31	2016
" why did the model fail?": Attributing model performance changes to distribution shifts H Zhang, H Singh, M Ghassemi, S Joshi	27	2023
What's fair is… fair? Presenting JustEFAB, an ethical framework for operationalizing medical ethics and social justice in the integration of clinical machine learning: JustEFAB M Mccradden, O Odusi, S Joshi, I Akrout, K Ndlovu, B Glocker, G Maicas, ... Proceedings of the 2023 ACM Conference on Fairness, Accountability, and …, 2023	23	2023
Pre-emptive learning-to-defer for sequential medical decision-making under uncertainty S Joshi, S Parbhoo, F Doshi-Velez arXiv preprint arXiv:2109.06312, 2021	20	2021
Sequential explanations with mental model-based policies A Yeung, S Joshi, JJ Williams, F Rudzicz arXiv preprint arXiv:2007.09028, 2020	16	2020
Counterfactually guided policy transfer in clinical settings TW Killian, M Ghassemi, S Joshi Conference on Health, Inference, and Learning, 5-31, 2022	13	2022

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