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2020 – today
- 2023
[c13]Kangning Liu, Weicheng Zhu, Yiqiu Shen, Sheng Liu, Narges Razavian, Krzysztof J. Geras, Carlos Fernandez-Granda:
Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning. CVPR 2023: 3355-3365- [i18]Weicheng Zhu, Sheng Liu, Carlos Fernandez-Granda, Narges Razavian:
Making Self-supervised Learning Robust to Spurious Correlation via Learning-speed Aware Sampling. CoRR abs/2311.16361 (2023) - [i17]Long Chen, Liben Chen, Binfeng Xu, Wenxin Zhang, Narges Razavian:
Automatic Detection of Alzheimer's Disease with Multi-Modal Fusion of Clinical MRI Scans. CoRR abs/2311.18245 (2023) - 2022
- [j6]Vincent J. Major, Simon Andrew Jones, Narges Razavian, Ashley Bagheri, Felicia Mendoza, Jay Stadelman, Leora I. Horwitz, Jonathan S. Austrian, Yindalon Aphinyanaphongs:
Evaluating the Effect of a COVID-19 Predictive Model to Facilitate Discharge: A Randomized Controlled Trial. Appl. Clin. Inform. 13(3): 632-640 (2022) - [c12]Sheng Liu, Aakash Kaku, Weicheng Zhu, Matan Leibovich, Sreyas Mohan, Boyang Yu, Haoxiang Huang, Laure Zanna, Narges Razavian, Jonathan Niles-Weed, Carlos Fernandez-Granda:
Deep Probability Estimation. ICML 2022: 13746-13781 - [c11]Weicheng Zhu, Carlos Fernandez-Granda, Narges Razavian:
Interpretable Prediction of Lung Squamous Cell Carcinoma Recurrence With Self-supervised Learning. MIDL 2022: 1504-1522 - [i16]Weicheng Zhu, Carlos Fernandez-Granda, Narges Razavian:
Interpretable Prediction of Lung Squamous Cell Carcinoma Recurrence With Self-supervised Learning. CoRR abs/2203.12204 (2022) - [i15]Kangning Liu, Weicheng Zhu, Yiqiu Shen
, Sheng Liu, Narges Razavian, Krzysztof J. Geras, Carlos Fernandez-Granda:
Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning. CoRR abs/2210.09452 (2022) - 2021
- [j5]Farah E. Shamout, Yiqiu Shen, Nan Wu, Aakash Kaku, Jungkyu Park, Taro Makino, Stanislaw Jastrzebski, Jan Witowski, Duo Wang, Ben Zhang, Siddhant Dogra, Meng Cao, Narges Razavian, David Kudlowitz, Lea Azour, William Moore, Yvonne W. Lui, Yindalon Aphinyanaphongs, Carlos Fernandez-Granda, Krzysztof J. Geras:
An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department. npj Digit. Medicine 4 (2021) - [c10]Weicheng Zhu, Narges Razavian:
Variationally regularized graph-based representation learning for electronic health records. CHIL 2021: 1-13 - [c9]Aakash Kaku, Sahana Upadhya, Narges Razavian:
Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning. NeurIPS 2021: 24063-24074 - [i14]Aakash Kaku, Sahana Upadhya, Narges Razavian:
Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning. CoRR abs/2110.14805 (2021) - [i13]Daniel Jiwoong Im, Kyunghyun Cho, Narges Razavian:
Causal Effect Variational Autoencoder with Uniform Treatment. CoRR abs/2111.08656 (2021) - [i12]Sheng Liu, Aakash Kaku, Weicheng Zhu, Matan Leibovich, Sreyas Mohan, Boyang Yu, Laure Zanna, Narges Razavian, Carlos Fernandez-Granda:
Deep Probability Estimation. CoRR abs/2111.10734 (2021) - 2020
- [j4]Narges Razavian, Vincent J. Major, Mukund Sudarshan, Jesse Burk-Rafel, Peter Stella, Hardev Randhawa, Seda Bilaloglu, Ji Chen, Vuthy Nguy, Walter Wang, Hao Zhang, Ilan Reinstein, David Kudlowitz, Cameron Zenger, Meng Cao, Ruina Zhang, Siddhant Dogra, Keerthi B. Harish, Brian Bosworth, Fritz Francois, Leora I. Horwitz, Rajesh Ranganath, Jonathan S. Austrian, Yindalon Aphinyanaphongs:
A validated, real-time prediction model for favorable outcomes in hospitalized COVID-19 patients. npj Digit. Medicine 3 (2020) - [c8]Zachariah Zhang, Jingshu Liu, Narges Razavian:
BERT-XML: Large Scale Automated ICD Coding Using BERT Pretraining. ClinicalNLP@EMNLP 2020: 24-34 - [c7]Xiaoyi Zhang, Rodoniki Athanasiadou, Narges Razavian:
Tracing State-Level Obesity Prevalence from Sentence Embeddings of Tweets: A Feasibility Study. Poly/DMAH@VLDB 2020: 141-150 - [c6]Sheng Liu, Jonathan Niles-Weed, Narges Razavian, Carlos Fernandez-Granda:
Early-Learning Regularization Prevents Memorization of Noisy Labels. NeurIPS 2020 - [i11]Zachariah Zhang, Jingshu Liu, Narges Razavian:
BERT-XML: Large Scale Automated ICD Coding Using BERT Pretraining. CoRR abs/2006.03685 (2020) - [i10]Sheng Liu, Jonathan Niles-Weed, Narges Razavian, Carlos Fernandez-Granda:
Early-Learning Regularization Prevents Memorization of Noisy Labels. CoRR abs/2007.00151 (2020) - [i9]Farah E. Shamout, Yiqiu Shen, Nan Wu, Aakash Kaku, Jungkyu Park, Taro Makino, Stanislaw Jastrzebski, Duo Wang, Ben Zhang, Siddhant Dogra, Meng Cao, Narges Razavian, David Kudlowitz, Lea Azour, William Moore, Yvonne W. Lui, Yindalon Aphinyanaphongs, Carlos Fernandez-Granda, Krzysztof J. Geras:
An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department. CoRR abs/2008.01774 (2020)
2010 – 2019
- 2019
- [c5]Sheng Liu, Chhavi Yadav, Carlos Fernandez-Granda, Narges Razavian:
On the design of convolutional neural networks for automatic detection of Alzheimer's disease. ML4H@NeurIPS 2019: 184-201 - [i8]Sheng Liu, Chhavi Yadav, Carlos Fernandez-Granda, Narges Razavian:
On the design of convolutional neural networks for automatic detection of Alzheimer's disease. CoRR abs/1911.03740 (2019) - [i7]Aakash Kaku, Chaitra V. Hegde, Jeffrey Huang, Sohae Chung, Xiuyuan Wang, Matthew Young, Alireza Radmanesh, Yvonne W. Lui, Narges Razavian:
DARTS: DenseUnet-based Automatic Rapid Tool for brain Segmentation. CoRR abs/1911.05567 (2019) - [i6]Josie Williams, Narges Razavian:
Towards Quantification of Bias in Machine Learning for Healthcare: A Case Study of Renal Failure Prediction. CoRR abs/1911.07679 (2019) - [i5]Xiaoyi Zhang, Rodoniki Athanasiadou, Narges Razavian:
Tracing State-Level Obesity Prevalence from Sentence Embeddings of Tweets: A Feasibility Study. CoRR abs/1911.11324 (2019) - [i4]Weicheng Zhu, Narges Razavian:
Graph Neural Network on Electronic Health Records for Predicting Alzheimer's Disease. CoRR abs/1912.03761 (2019) - 2018
- [c4]Jingshu Liu, Zachariah Zhang, Narges Razavian:
Deep EHR: Chronic Disease Prediction Using Medical Notes. MLHC 2018: 440-464 - [i3]Jingshu Liu, Zachariah Zhang, Narges Razavian:
Deep EHR: Chronic Disease Prediction Using Medical Notes. CoRR abs/1808.04928 (2018) - 2016
- [c3]Narges Razavian, Jake Marcus, David A. Sontag:
Multi-task Prediction of Disease Onsets from Longitudinal Laboratory Tests. MLHC 2016: 73-100 - [i2]Narges Razavian, Jake Marcus, David A. Sontag:
Multi-task Prediction of Disease Onsets from Longitudinal Lab Tests. CoRR abs/1608.00647 (2016) - 2015
- [j3]Narges Razavian, Saul Blecker, Ann Marie Schmidt, Aaron Smith-McLallen, Somesh Nigam, David A. Sontag:
Population-Level Prediction of Type 2 Diabetes From Claims Data and Analysis of Risk Factors. Big Data 3(4): 277-287 (2015) - [j2]Narges Razavian:
Advancing the frontier of data-driven healthcare. XRDS 21(4): 34-37 (2015) - [c2]Josua Krause, Narges Razavian, Enrico Bertini, David A. Sontag:
Visual Exploration of Temporal Data in Electronic Medical Records. AMIA 2015 - [c1]Narges Razavian, Saul Blecker, David A. Sontag:
Gaussian Processes for interpreting Multiple Prostate Specific Antigen measurements for Prostate Cancer Prediction. AMIA 2015 - [i1]Narges Razavian, David A. Sontag:
Temporal Convolutional Neural Networks for Diagnosis from Lab Tests. CoRR abs/1511.07938 (2015) - 2013
- [b1]Narges Razavian:
Continuous Graphical Models for Static and Dynamic Distributions: Application to Structural Biology. Carnegie Mellon University, USA, 2013 - 2012
- [j1]Narges Razavian, Hetunandan Kamisetty, Christopher James Langmead:
Learning generative models of molecular dynamics. BMC Genom. 13(S-1): S5 (2012)
Coauthor Index
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