Tuesday August 25th, Tutorials (all times listed are CDT)


Tutorial 1: Methods and Applications of Natural Language Processing in Medicine


Tutorial 2: Large Scale Ensembled NLP Systems with Docker and Kubernetes


Tutorial 3: The Overview Effect: Clinical Medicine and Healthcare Concepts for the Data Scientist

Wednesday August 26th, Doctoral Consortium and Coronavirus-Themed Workshop (all times listed are CDT)


Workshop 1: Artificial Intelligence and the Coronavirus


Doctoral Consortium

Thursday August 27th, Main Conference Day 1 (all times listed are CDT)
(L) 20 minute presentation, (S) 5 minute presentation




Opening (Chairs: Martin Michalowski and Robert Moskovitch)


Welcome Address (University of Minnesota President Joan Gabel)


Keynote 1 (Chairs: Martin Michalowski & Robert Moskovitch)

Dr. Edward H. Shortliffe: AI Today: Are We Forgetting Our Roots


Predictive Modeling I (Chair: Mary Boland) (2 long presentations)

1. Fattaneh Jabbari, Liza C. Villaruz, Mike Davis and Gregory F. Cooper: Lung Cancer Survival Prediction Using Instance-specific Bayesian Networks (L)

2. Paolo Fraccaro, Xenophon Evangelopoulos and Blair Edwards: Development and preliminary evaluation of a method for passive, privacy-aware home care monitoring based on 2D LiDAR data (L)


Break (20 minutes)


Poster Presentations (Chair: Martin Michalowski) (9 short presentations)

1. Pietro Bosoni, Marco Meccariello, Valeria Calcaterra, Cristiana Larizza, Lucia Sacchi and Riccardo Bellazzi: Deep learning applied to blood glucose prediction from Flash Glucose Monitoring and Fitbit data (S)

2. Omar El Rifai, Imen Megdiche, Olivier Teste, Franck Ravat, Maëlle Biotteau and Xavier de Boissezon: Blockchain-based Federated Learning in Medecine (S)

3. Olgierd Unold, Mateusz Gabor and Witold Dyrka: Unsupervised grammar induction for revealing the internal structure of protein sequence motifs (S)

4. Anita Valmarska, Dragana Miljkovic, Nada Lavrač and Marko Robnik-Sikonja: Multi-view clustering with mvReliefF for Parkinson's disease patients subgroup detection (S)

5. Hossein Estiri, Sebastien Vasey and Shawn Murphy: Transitive sequential pattern mining for discrete clinical records (S)

6. Miriam Santos, Pedro Abreu, Szymon Wilk and João Santos: Assessing the impact of distance functions on k-nearest neighbour imputation of biomedical datasets (S)

7. Shazia Afzal, Tejas Indulal Dhamecha, Paul Gagnon, Akash Nayak, Ayush Shah, Jan Carlstedt-Duk, Smriti Pathak, Sneha Mondal, Akshay Gugnani, Nabil Zary and Malolan Chetlur: AI Medical School Tutor: Modelling and Implementation (S)

8. Theodoros Tsiligkaridis and Jennifer Sloboda: A Multi-Task LSTM Framework for Improved Early Sepsis Prediction (S)

9. Jing Ke, Yiqing Shen, Yi Guo and Jason D. Wright: A High-throughput Tumor Location System with Deep Learning for Colorectal Cancer Histopathology Image (S)


Unsupervised Learning and Bioinformatics (Chair: Wojtek Michalowski) (2 long presentations)

1. Tom Mahler, Erez Shalom, Yuval Elovici and Yuval Shahar: A Dual-Layer Architecture for the Protection of Medical Devices from Anomalous Instructions (L)

2. Matthew Casey and Nianjun Zhou: Analysis of Viability of TCGA and GTEx Gene Expression for Gleason Grade Identification (L)


Lunch + Poster Session (1 hour)


Temporal Data Analysis I (Chair: Robert Moskovitch) (5 presentations: 5 long)

1. Jeong Min Lee and Milos Hauskrecht: Multi-scale Temporal Memory for Clinical Event Time-Series Prediction (L)

2. Ariane Morassi Sasso, Suparno Datta, Michael Jeitler, Christian S. Kessler, Bert Arnrich and Erwin Boettinger: HYPE: Predicting Blood Pressure from Photoplethysmograms in a Hypertensive Population (L) (Best student paper candidate)

3. Cheng Cheng, Helen Zhou, Zachary Lipton, George Chen and Jeremy Weiss: Mortality Risk Score for Critically Ill Patients with Viral or Unspecified Pneumonia: Assisting COVID-19 Clinicians with ECMO Planning (L)

4. Tianran Zhang, Muhao Chen and Alex Bui: Diagnostic Prediction with Sequence-of-sets Representation Learning for Clinical Event (L)

5. Peter Svenson, Giannis Haralabopoulos and Mercedes Torres Torres: Sepsis Deterioration Prediction Using Channelled Long Short-Term Memory Networks (L) 


Break (20 minutes)


Predictive Modeling II (Chair: Nitesh Chawla) (4 long presentations)

1. Ying Zhu, Roshan Tourani, Adam Sheka, Elizabeth Wick, Genevieve Melton and Gyorgy Simon: Innovative method to build robust prediction models when gold-standard outcomes are scarce (L)

2. Roshan Tourani, Dennis Murphree, Ying Zhu, Adam Sheka, Genevieve Melton, Daryl Kor and Gyorgy Simon: Consensus modeling: a transfer learning approach for small health systems (L) (Best paper candidate)

3. Jaber Rad, Calvino Cheng, Jason G Quinn and Syed Sibte Raza Abidi: An AI-Driven Predictive Modelling Framework to Analyze and Visualize Blood Product Transactional Data for Reducing Blood
Products’ Discards

4. Tomer Sagi, Emil Riis Hansen, Katja Hose, Gregory Y. H. Lip, Torben Bjerregaard Larsen and Flemming Skjøth: Towards Assigning Diagnosis Codes using Medication History (L) (Best paper candidate)


Clinical Practice Guidelines (Chair: Martin Michalowski) (2 long presentations)

1. Nick Fung, Marten van Sinderen, Valerie Jones and Hermie Hermens: A verified, executable formalism for resilient and pervasive guideline-based decision support for patients (L)

2. William Van Woensel, Samina Abidi, Borna Jafarpour and Syed Sibte Raza Abidi: A CIG Integration Framework to Provide Decision Support for Comorbid Conditions using Transaction-based Semantics and Temporal Planning (L)


Deep Learning (Chair: Fei Wang) (4 long presentations)

1. Pavel Novitski, Cheli Melzer Cohen, Gabriel Hodik, Avraham Karasik, Varda Botvinik and Robert Moskovitch: All-Cause Mortality Prediction in T2D Patients with iTirps (L)

2. Tingyi Wanyan, Martin Kang, Marcus Badgeley, Kipp Johnson, Jessica De Freitas, Fayzan Chaudhry, Akhil Vaid, Shan Zhao, Riccardo Miotto, Girish Nadkarni, Fei Wang, Justin Rousseau, Ariful Azad, Ying Ding and Benjamin Glicksberg: Heterogenous Graph Embeddings of Electronic Health Record Data Improve Critical Care Disease Predictions (L)

3. Gabriel Schamberg, Marcus Badgeley and Emery N. Brown: Controlling Level of Unconsciousness by Titrating Propofol with Deep Reinforcement Learning (L) (Best paper candidate)

4. Sina Rashidian, Fusheng Wang, Richard Moffitt, Victor Garcia, Anurag Dutt, Wei Chang, Vishwam Pandya, Janos Hajagos, Mary Saltz and Joel Saltz: HealthGAN: Towards Sharp and Smooth Synthetic EHR Data Generation (L)

Friday August 28th, Main Conference Day 2 (all times listed are CDT)
(L) 20 minute presentation, (S) 5 minute presentation


Panel: AI in the Time of Coronavirus (Moderator: Robert Moskovitch)


1. Dr. David Buckeridge, McGill University, Canada

2. Dr. Mengchun Gong, Digital China Health Technology, China

3. Dr. Laurence Lovat, University College London Hospitals, UK

4. Dr. Orly Weinstein, Clalit Healthcare Services, Israel

5. Dr. Glenn Kramer, xCures, USA


Keynote 2 (Chairs: Robert Moskovitch & Martin Michalowski)

Dr. Vimla L. Patel: Human Cognition: A Guide to Evolution of AI


Break (20 minutes)


Temporal Data Analysis II (Chair: John H. Holmes) (4 long presentations)

1. Linhong Li, Ren Zuo, Amanda Coston, Jeremy Weiss and George Chen: Neural Topic Models with Survival Supervision: Jointly Predicting Time-to-Event Outcomes and Learning How Clinical Features Relate (L)

2. Saloni Saloni Dash, Andrew Yale, Isabelle Guyon and Kristin Bennett: Medical Time-Series Data Generation using Generative Adversarial Networks (L)

3. Nevo Itzhak, Aditya Nagori, Edo Lior, Maya Schvetz, Tavpritesh Sethi and Robert Moskovitch: Continuous Prediction of Acute Hypertensive Episodes in ICU Data (L) (Best student paper candidate)

4. Ofir Dvir, Paul Wolfson, Laurence Lovat and Robert Moskovitch: Falls Prediction in Care Homes Using a Mobile App Data Collection (L)


Lunch + Poster Session (1 hour 20 minutes)


Natural Language Processing (Chair: Serguei Pakhomov) (6 long presentations)

1. Anusha Bompelli, Greg Silverman, Raymond Finzel, Jake Vasilakes, Benjamin Knoll, Serguei Pakhomov and Rui Zhang: Comparing NLP Systems to Extract Entities of Eligibility Criteria in Dietary Supplements Clinical Trials using NLP-ADAPT (L)

2. Mahdi Abdollahi, Xiaoying Gao, Yi Mei, Shameek Ghosh and Jinyan Li: Ontology-guided data augmentation for medical document classification (L)

3. Pavel Blinov, Manvel Avetisian, Vladimir Kokh, Dmitry Umerenkov and Alexander Tuzhilin: Predicting Clinical Diagnosis from Patients Electronic Health Records Using BERT-based Neural Networks (L)

4. Mohammed Ali Al-Garadi, Yuan-Chi Yang, Sahithi Lakamana, Jie Lin, Sabrina Li, Angel Xie, Whitney Hogg-Bremer, Mylin Torres, Imon Banerjee and Abeed Sarker: Automatic Breast Cancer Cohort Detection from Social Media for Studying Factors Affecting Patient Centered Outcomes (L)

5. Yves Mercadier, Jérôme Azé and Sandra Bringay: Divide to better classify (L) (Best student paper candidate)

6. Konstantinos Bougiatiotis, Fotis Aisopos, Anastasios Nentidis, Anastasia Krithara and George Paliouras: Drug-Drug Interaction Prediction on a Biomedical Literature Knowledge Graph (L)


Break (20 minutes)


Information Retrieval and Image Processing (Chair: Martin Michalowski) (5 long presentations)

1. Antonio Sze-To and Hamid Tizhoosh: Searching pneumothorax among half a million chest X-ray images (L)

2. Morteza Babaie, Hany Kashani, Meghana D. Kumar and H. R. Tizhoosh: A New Local Radon-Based Descriptor For Content-Based Image Search (L)

3. Aditya Sriram, Shivam Kalra, Morteza Babaie, Brady Kieffer, W. Al Drobi, Shahryar Rahnamayan, Hany Kashani and Hamid Tizhoosh: Forming Local Intersections of Projections for Classifying and Searching Histopathology Images (L)

4. Jerry Wei, Arief Suriawinata, Xiaoying Liu, Bing Ren, Mustafa Nasir-Moin, Naofumi Tomita, Jason Wei and Saeed Hassanpour: Difficulty Translation in Colorectal Histopathology Images (L)

5. Mariia Dobko, Ostap Viniavskyi and Oles Dobosevych: Weakly-Supervised Segmentation for Disease Localization in Chest X-Ray Images (L)


Closing (Chair: Martin Michalowski & Robert Moskovitch)