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Joseph D. Janizek
Joseph D. Janizek
MD / CSE PhD Student, University of Washington
Verified email at uw.edu - Homepage
Title
Cited by
Cited by
Year
Accurate classification of BRCA1 variants with saturation genome editing
GM Findlay, RM Daza, B Martin, MD Zhang, AP Leith, M Gasperini, ...
Nature 562 (7726), 217-222, 2018
6772018
AI for radiographic COVID-19 detection selects shortcuts over signal
AJ DeGrave, JD Janizek, SI Lee
Nature Machine Intelligence 3 (7), 610-619, 2021
5002021
Improving performance of deep learning models with axiomatic attribution priors and expected gradients
G Erion, JD Janizek, P Sturmfels, S Lundberg, SI Lee
Nature Machine Intelligence, 2019
252*2019
True to the Model or True to the Data?
H Chen, JD Janizek, S Lundberg, SI Lee
ICML Workshop on Human Interpretability in Machine Learning, 2020
1482020
Explaining explanations: Axiomatic feature interactions for deep networks
JD Janizek, P Sturmfels, SI Lee
Journal of Machine Learning Research 22 (104), 1-54, 2021
1242021
Adversarial deconfounding autoencoder for learning robust gene expression embeddings
AB Dincer, JD Janizek, SI Lee
Bioinformatics 36 (Supplement_2), i573-i582, 2020
482020
Explainable machine learning prediction of synergistic drug combinations for precision cancer medicine
JD Janizek, S Celik, SI Lee
ICML Workshop on Computational Biology, 331769, 2018
442018
An adversarial approach for the robust classification of pneumonia from chest radiographs
JD Janizek, G Erion, AJ DeGrave, SI Lee
Proceedings of the ACM conference on health, inference, and learning, 69-79, 2020
272020
Learning Deep Attribution Priors Based On Prior Knowledge
E Weinberger, J Janizek, SI Lee
(NeurIPS 2020) Advances in Neural Information Processing Systems 33, 2019
252019
A cost-aware framework for the development of AI models for healthcare applications
G Erion, JD Janizek, C Hudelson, RB Utarnachitt, AM McCoy, MR Sayre, ...
Nature Biomedical Engineering 6 (12), 1384-1398, 2022
21*2022
Uncovering expression signatures of synergistic drug responses via ensembles of explainable machine-learning models
JD Janizek, AB Dincer, S Celik, H Chen, W Chen, K Naxerova, SI Lee
Nature Biomedical Engineering 7 (6), 811-829, 2023
13*2023
PAUSE: principled feature attribution for unsupervised gene expression analysis
JD Janizek, A Spiro, S Celik, BW Blue, JC Russell, TI Lee, M Kaeberlin, ...
Genome Biology 24 (1), 81, 2023
8*2023
Auditing the inference processes of medical-image classifiers by leveraging generative AI and the expertise of physicians
AJ DeGrave, ZR Cai, JD Janizek, R Daneshjou, SI Lee
Nature Biomedical Engineering, 1-13, 2023
6*2023
A deep profile of gene expression across 18 human cancers
W Qiu, AB Dincer, J Janizek, S Celik, M Pittet, K Naxerova, SI Lee
bioRxiv, 2024.03. 17.585426, 2024
2024
Understanding Biomedical Machine Learning Models
JD Janizek
University of Washington, 2022
2022
Course Corrections for Clinical AI
AJ DeGrave, JD Janizek, SI Lee
Kidney360 2 (12), 2019-2023, 2021
2021
AI for radiographic COVID-19 detection selects shortcuts over signal (preprint)
AJ DeGrave, JD Janizek, SI Lee
2020
Characterization of the Lipase Stimulating Domain for Apolipoprotein AV and the Development of a Therapeutic Peptide for the Treatment of Hypertriglyceridemia
JD Janizek, K Munro, MH Davidson, JB Ancsin
Arteriosclerosis, Thrombosis, and Vascular Biology 35 (suppl_1), A537-A537, 2015
2015
A Novel Fluorescence-Based Assay is Used to Investigate the Triglyceride Hydrolytic Activity of Lipases and to Identify Synthetic Peptides With Strong Lipase-Stimulating Activities
JD Janizek, K Munro, MH Davidson, JB Ancsin
Arteriosclerosis, Thrombosis, and Vascular Biology 34 (suppl_1), A31-A31, 2014
2014
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Articles 1–19