Welcome to the journal club for the Department of Biomedical Informatics at Emory University.

We present and critique literature on machine learning, signal processing, and computation in biomedicine.

Sessions are moderated by Professor Shamim Nemati.


Biomedical Informatics Conference Room
Woodruff Memorial Research Building (WMB)
101 Woodruff Circle,
Atlanta, GA 30322

Schedule & Papers

Date Time Presenter PDFs of Papers & Slides ( )
02/25 3pm Matt Temporal Convolutional Networks and Dynamic Time Warping can Drastically Improve the Early Prediction of Sepsis
02/11 3pm Russell Sepsis as a model for improving diagnosis and Evaluating the impact of a computerized surveillance algorithm and decision support system on sepsis mortality
02/07 4pm Supreeth Exponentially Weighted Imitation Learning for Batched Historical Data
01/09 3pm Russell Evaluating a New Marker for Risk Prediction Using the Test Tradeoff: An Update Decision Analysis for the Evaluation of Diagnostic Tests, Prediction Models, and Molecular Markers Decision Analysis
12/05 4pm Russell The challenge of implementing AI models in the ICU To Trust Or Not To Trust A Classifier Supplement
11/16 2pm Russell/Supreeth Relational inductive biases, deep learning, and graph networks
10/24 1pm Russell The Artificial Intelligence Clinician learns optimal treatment strategies for sepsis in intensive care Supplementary Materials
10/03 1pm Supreeth Addressing Appearance Change in Outdoor Robotics with Adversarial Domain Adaptation
09/28 11am Supreeth Estimating attributable fraction of mortality from sepsis to inform clinical trials Supplementary Materials
09/12 3pm Russell The reusable holdout: Preserving validity in adaptive data analysis Supplementary Materials

SEPSIS Grand Rounds

Date Time Presenter PDFs of Papers & Slides ( )
09/23 11am Chris Control of Confounding and Reporting of Results in Causal Inference Studies Examples of DAG Strobe Statement Strobe Paper

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Previous presentations

Date Presenter PDFs of Papers & Slides ( )
03/07 Supreeth Scalable and accurate deep learning for Electronic Health Records
01/31 Supreeth Learning to cluster in order to transfer across domains and tasks
01/24 Azade Maximum Likelihood Estimation, Weibull cox proportional hazards model
12/14/17 Supreeth Neural Network based clustering using pair-wise constraints
07/13/17 Erik Reinertsen Transfer Entropy Estimation and Directional Coupling Change Detection in Biomedical Time Series
07/06/17 Supreeth Doubly Robust Policy Evaluation and Learning
06/29/17 Supreeth Doubly Robust Estimation of Causal Effects
06/22/17 Supreeth Nonlinear Inverse Reinforcement Learning with Gaussian Processes
06/07/17 Supreeth Doctor AI: Predicting Clinical Events via Recurrent Neural Networks
06/22/16 Mark Connolly The Automatic Neuroscientist: A framework for optimizing experimental design with closed-loop real-time fMRI
05/18/16 Sahar Harati Speech Emotion Recognition Using Deep Neural Network and Extreme Learning Machine
04/27/16 Jitesh Punjabi Using Anchors to Estimate Clinical State without Labelee Data
04/13/16 Supreeth Prajwal OrderRex: clinical order decision support and outcome predictions by data-mining electronic medical records
03/30/16 Ziyi Li Using generalized estimating equations for longitudinal data analysis
03/02/16 Erik Reinertsen Major depressive disorder subtypes to predict long-term course
02/17/16 Myles McCrary Real-time prediction of mortality, readmission, and length of stay