Narges Razavian

According to our database, Narges Razavian authored at least 30 papers between 2012 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Automatic Detection of Alzheimer's Disease with Multi-Modal Fusion of Clinical MRI Scans.

Long Chen, Liben Chen, Binfeng Xu, Wenxin Zhang, Narges Razavian

CoRR, 2023

Making Self-supervised Learning Robust to Spurious Correlation via Learning-speed Aware Sampling.

Weicheng Zhu, Sheng Liu, Carlos Fernandez-Granda, Narges Razavian

CoRR, 2023

Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning.

Kangning Liu, Weicheng Zhu, Yiqiu Shen, Sheng Liu, Narges Razavian, Krzysztof J. Geras, Carlos Fernandez-Granda

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Evaluating the Effect of a COVID-19 Predictive Model to Facilitate Discharge: A Randomized Controlled Trial.

Vincent J. Major, Simon Andrew Jones, Narges Razavian, Ashley Bagheri, Felicia Mendoza, Jay Stadelman, Leora I. Horwitz, Jonathan S. Austrian, Yindalon Aphinyanaphongs

Appl. Clin. Inform., May, 2022

Interpretable Prediction of Lung Squamous Cell Carcinoma Recurrence With Self-supervised Learning.

Weicheng Zhu, Carlos Fernandez-Granda, Narges Razavian

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

Deep Probability Estimation.

Sheng Liu, Aakash Kaku, Weicheng Zhu, Matan Leibovich, Sreyas Mohan, Boyang Yu, Haoxiang Huang, Laure Zanna, Narges Razavian, Jonathan Niles-Weed, Carlos Fernandez-Granda

Proceedings of the International Conference on Machine Learning, 2022

2021

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department.

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

npj Digit. Medicine, 2021

Deep Probability Estimation.

Sheng Liu, Aakash Kaku, Weicheng Zhu, Matan Leibovich, Sreyas Mohan, Boyang Yu, Laure Zanna, Narges Razavian, Carlos Fernandez-Granda

CoRR, 2021

Causal Effect Variational Autoencoder with Uniform Treatment.

Daniel Jiwoong Im, Kyunghyun Cho, Narges Razavian

CoRR, 2021

Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning.

Aakash Kaku, Sahana Upadhya, Narges Razavian

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Variationally regularized graph-based representation learning for electronic health records.

Weicheng Zhu, Narges Razavian

Proceedings of the ACM CHIL '21: ACM Conference on Health, 2021

2020

A validated, real-time prediction model for favorable outcomes in hospitalized COVID-19 patients.

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

npj Digit. Medicine, 2020

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department.

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

CoRR, 2020

Early-Learning Regularization Prevents Memorization of Noisy Labels.

Sheng Liu, Jonathan Niles-Weed, Narges Razavian, Carlos Fernandez-Granda

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Tracing State-Level Obesity Prevalence from Sentence Embeddings of Tweets: A Feasibility Study.

Xiaoyi Zhang, Rodoniki Athanasiadou, Narges Razavian

Proceedings of the Heterogeneous Data Management, Polystores, and Analytics for Healthcare, 2020

BERT-XML: Large Scale Automated ICD Coding Using BERT Pretraining.

Zachariah Zhang, Jingshu Liu, Narges Razavian

Proceedings of the 3rd Clinical Natural Language Processing Workshop, 2020

2019

Graph Neural Network on Electronic Health Records for Predicting Alzheimer's Disease.

Weicheng Zhu, Narges Razavian

CoRR, 2019

Towards Quantification of Bias in Machine Learning for Healthcare: A Case Study of Renal Failure Prediction.

Josie Williams, Narges Razavian

CoRR, 2019

DARTS: DenseUnet-based Automatic Rapid Tool for brain Segmentation.

Aakash Kaku, Chaitra V. Hegde, Jeffrey Huang, Sohae Chung, Xiuyuan Wang, Matthew Young, Alireza Radmanesh, Yvonne W. Lui, Narges Razavian

CoRR, 2019

On the design of convolutional neural networks for automatic detection of Alzheimer's disease.

Sheng Liu, Chhavi Yadav, Carlos Fernandez-Granda, Narges Razavian

Proceedings of the Machine Learning for Health Workshop, 2019

2018

Deep EHR: Chronic Disease Prediction Using Medical Notes.

Jingshu Liu, Zachariah Zhang, Narges Razavian

Proceedings of the Machine Learning for Healthcare Conference, 2018

2016

Multi-task Prediction of Disease Onsets from Longitudinal Lab Tests.

Narges Razavian, Jake Marcus, David A. Sontag

CoRR, 2016

Multi-task Prediction of Disease Onsets from Longitudinal Laboratory Tests.

Narges Razavian, Jake Marcus, David A. Sontag

Proceedings of the 1st Machine Learning in Health Care, 2016

2015

Advancing the frontier of data-driven healthcare.

Narges Razavian

XRDS, 2015

Temporal Convolutional Neural Networks for Diagnosis from Lab Tests.

Narges Razavian, David A. Sontag

CoRR, 2015

Population-Level Prediction of Type 2 Diabetes From Claims Data and Analysis of Risk Factors.

Narges Razavian, Saul Blecker, Ann Marie Schmidt, Aaron Smith-McLallen, Somesh Nigam, David A. Sontag

Big Data, 2015

Gaussian Processes for interpreting Multiple Prostate Specific Antigen measurements for Prostate Cancer Prediction.

Narges Razavian, Saul Blecker, David A. Sontag

Proceedings of the AMIA 2015, 2015

Visual Exploration of Temporal Data in Electronic Medical Records.

Josua Krause, Narges Razavian, Enrico Bertini, David A. Sontag

Proceedings of the AMIA 2015, 2015

2013

Continuous Graphical Models for Static and Dynamic Distributions: Application to Structural Biology.

Narges Razavian

PhD thesis, 2013

2012

Learning generative models of molecular dynamics.

Narges Razavian, Hetunandan Kamisetty, Christopher James Langmead

BMC Genom., 2012