Narges Razavian

发表

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

Nan Wu, Ben Zhang, Farah E. Shamout, 2020, ArXiv.

Temporal Convolutional Neural Networks for Diagnosis from Lab Tests pdf

David Sontag, Narges Razavian, D. Sontag, 2015, ArXiv.

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

Narges Razavian, Weicheng Zhu, N. Razavian, 2019, ArXiv.

The von Mises Graphical Model: Expectation Propagation for Inference (CMU-CS-11-130/CMU-CB-11-102)

Hetunandan Kamisetty, Christopher J. Langmead, Narges Razavian, 2011 .

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

David Sontag, Narges Razavian, Saul Blecker, 2015, AMIA.

Visual Exploration of Temporal Data in Electronic Medical Records

Enrico Bertini, Josua Krause, David Sontag, 2015, AMIA.

Time-Varying Gaussian Graphical Models of Molecular Dynamics Data

Arvind Ramanathan, Subhodeep Moitra, Hetunandan Kamisetty, 2010 .

Efficient pan-cancer whole-slide image classification and outlier detection using convolutional neural networks

Aristotelis Tsirigos, Nicolas Coudray, Seda Bilaloglu, 2019, bioRxiv.

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

Narges Razavian, Xiaoyi Zhang, Rodoniki Athanasiadou, 2019, ArXiv.

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

David Sontag, Narges Razavian, Jake Marcus, 2016, ArXiv.

Using Brain MRI Images to Predict Memory, BMI & Age

Narges Razavian, Chhavi Yadav, 2019, 2019 IEEE International Conference on Humanized Computing and Communication (HCC).

Early-Learning Regularization Prevents Memorization of Noisy Labels pdf

Sheng Liu, Carlos Fernandez-Granda, Jonathan Niles-Weed, 2020, NeurIPS.

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

Narges Razavian, N. Razavian, 2013 .

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

Jeffrey Huang, Yvonne W. Lui, Aakash Kaku, 2019, ArXiv.

Multi-task Prediction of Disease Onsets from Longitudinal Laboratory Tests

David Sontag, Narges Razavian, Jake Marcus, 2016, MLHC.

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

Sheng Liu, Carlos Fernandez-Granda, Narges Razavian, 2019, ML4H@NeurIPS.

Deep EHR: Chronic Disease Prediction Using Medical Notes pdf

Zachariah Zhang, Jingshu Liu, Narges Razavian, 2018, MLHC.

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

David A. Sontag, Narges Razavian, Ann Marie Schmidt, 2015, Big Data.

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

Narges Razavian, Josie Williams, N. Razavian, 2019, ArXiv.

Learning generative models of molecular dynamics

Christopher James Langmead, Hetunandan Kamisetty, Narges Razavian, 2012, BMC Genomics.

Advancing the frontier of data-driven healthcare

Narges Razavian, 2015, XRDS.

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

Zachariah Zhang, Jingshu Liu, Narges Razavian, 2020, ClinicalNLP@EMNLP.

Artificial intelligence and cancer

Anne E Carpenter, Olga G. Troyanskaya, Anne E. Carpenter, 2020, Nature Cancer.

Causal Effect Variational Autoencoder with Uniform Treatment pdf

Daniel Jiwoong Im, Narges Razavian, Kyunghyun Cho, 2021, arXiv.org.

Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning pdf

Aakash Kaku, Narges Razavian, Sahana Upadhya, 2021, NeurIPS.

Variationally regularized graph-based representation learning for electronic health records

Narges Razavian, Weicheng Zhu, 2021, CHIL.

Deep Probability Estimation pdf

Carlos Fernandez-Granda, Matan Leibovich, Sreyas Mohan, 2021, ArXiv.

Early Detection of Diabetes from Health Claims

Youngduck Choi, Rahul G. Krishnan, Narges Razavian, 2013 .

P1.09-32 Classification and Mutation Prediction from Non-Small Cell Lung Cancer Histopathology Images Using Deep Learning

Aristotelis Tsirigos, David Fenyö, Theodore Sakellaropoulos, 2018, Journal of Thoracic Oncology.

Abstract 5309: Determining EGFR and STK11 mutational status in lung adenocarcinoma histopathology images using deep learning

Aristotelis Tsirigos, David Fenyö, Theodore Sakellaropoulos, 2018 .

Classification and Mutation Prediction from Non-Small Cell Lung Cancer Histopathology Images using Deep Learning

Aristotelis Tsirigos, David Fenyö, Theodore Sakellaropoulos, 2017, bioRxiv.

The von Mises Graphical Model: Regularized Structure and Parameter Learning (CMU-CS-11-129/CMU-CB-11-101)

Hetunandan Kamisetty, Christopher J. Langmead, Narges Razavian, 2011 .