Poster Sessions

POSTER SESSION 1 (10:30 - 11:00)


Predicting Patient Outcomes using Learning Edit Costs based on Stochastics Finite-State Transducers.

Abiel Roche-Lima, Nelson Schwarz, Adnel Figueroa-Jiménez, Leonardo Garcia-Lebron and Patricia Ordóñez


Predicting Patient State-of-Health using Sliding Window and Recurrent Classifiers

Adam McCarthy and Chris Williams


A Semi-Markov Switching Linear Gaussian Model for Censored Physiological Data

Ahmed Alaa, Jinsung Yoon, Scott Hu and Mihaela Van Der Schaar


Probabilistic intensity normalization of PET/SPECT images using Variational mixture of Gamma distributions.

Alberto Llera, Ismael Huertas, Pablo Mir and Christian Beckmann


Large scale modeling of antimicrobial resistance with interpretable classifiers

Alexandre Drouin, Frédéric Raymond, Gaël Letarte St-Pierre, Mario Marchand, Jacques Corbeil and François Laviolette


Bridging Medical Data Inference to Achilles Tendon Rupture Rehabilitation

An Qu, Cheng Zhang, Paul Ackermann and Hedvig Kjellström


Walking That Extra Mile: Robust Classification of Cardiac Condition with Semi-supervised Denoising from Heart Sound Recordings.

Arijit Ukil, Soma Bandyopadhyay, Chetanya Puri, Rituraj Singh, Arpan Pal and Debayan Mukherjee


A Fully Automated Pipeline for Detection and Segmentation of Liver Lesions and Pathological Lymph Nodes.

Assaf Hoogi, John  Lambert, Yefeng Zheng, Dorin Comaniciu and Daniel Rubin


Fusion of Transferred Convolutional Neural Network Features and Radiomic Features for Breast Cancer Diagnosis.

Benjamin Huynh and Maryellen Giger


Semi-Supervised Sequence Learning for Continuous Digital Biomarkers.

Brandon Ballinger, Johnson Hsieh, Nimit Sohoni, Greg Marcus, Jose Sanchez, Geoff Tison and Jeff Olgin


Stratified Locality-Sensitive Hashing for Sublinear Time Critical Event Prediction.

Bryce Kim, Erik Hemberg and Una-May O'Reilly


Multi-stage clustering of Breast Cancer for Precision Medicine

Chenzhe Qian


Survival Prediction with Limited Features: a Top Performing Approach from the DREAM ALS Stratification Prize4Life Challenge

Christoph Kurz


A simple squared-error reformulation for ordinal classification

Christopher Beckham and Christopher Pal


Canoni calcorrelation analysis for analyzing sequences of medical billing codes

Corinne Jones, Sham Kakade, Lucas Thornblade, David Flum and Abraham Flaxman


Generative Adversarial Networks for Medical Decision Modelling.

Cristóbal Esteban and Volker Tresp


Deep Learning for Suicidal Ideation Prediction.

Cristóbal Esteban, Antonio Artés and Volker Tresp


Control Matching via Discharge Code Sequences

Dang Nguyen, Wei Luo, Dinh Phung and Svetha Venkatesh


Breast Mass Classification from Mammograms using Deep Convolutional Neural Networks.

Daniel Lévy and Arzav Jain


Bayesian latent variable modelling to accelerate endotype discovery in asthma and allergic diseases.

Danielle Belgrave, Raquel Granell, John Guiver, Christopher Bishop, Iain Buchan,

Angela Simpson, John Henderson and Adnan Custovic


A Bayesian Approach to Predicting Disengaged Youth

David Kohn, Sally Cripps, Nick Glozier and Hugh Durrant-Whyte


Machine Learning in Textual Data of Cardiovascular Disease via Phrase Mining and Network Embedding.

David Liem, Doris Xin, Vincent Kyi, Quan Cao, Leah Briscoe, Fangbo Tao, Karol Watson, Jiawei Han and Peipei Ping


Understanding Anatomy Classification Through Visualization

Devinder Kumar and Vlado Menkovski


A deep learning framework to predict survival from medical images of lung cancer patients.

Edward Lee, Mu Zhou, Olya Grove, Yoganand Balagurunathan, Sebastian Echegaray, Robert Robert Gillies, Noah Gamboa, Boris Murmann, Sandy Napel, Simon Wong and Olivier Gevaert


Transfer Learning via Latent Factor Modeling to Improve Prediction of Surgical Complications.  Elizabeth Lorenzi, Zhifei Sun, Erich Huang, Ricardo Henao and Katherine Heller


A new pediatric early warning score: predicting rare events using medical record data in real time.

Erika Strandberg, Catherine Ross, Natalie Pageler and Mohsen Bayati


Demographical Priors for Health Conditions Diagnosis Using Medicare Data

Fahad Alhasoun, May Alhazzani and Marta Gonzalez


Challenges and preliminary outcomes of real world data analytics based on the national e-prescription of Greece: The use case of Diabetes Mellitus.

George Dafoulas, Stavros Liatis, Petros Sfikakis and Konstantinos Makrilakis


Time-series clustering for discovering trajectories of physiological deterioration in post-operative care.

Hamish Tomlinson, Marco Pimentel, Peter Watkinson and Lionel Tarassenko


The Use of Autoencoders for Discovering Patient Phenotypes.

Harini Suresh and Marzyeh Ghassemi


Estimation of Basic Reproduction Number R0 using a Recurrent Neural Network.

Heidi Tessmer and Ryosuke Omori



POSTER SESSION 2 (3:00 - 3:30)


Learning Cost-Effective and Interpretable Treatment Regimes

Himabindu Lakkaraju and Cynthia Rudin


Computerized Multiparametric MR image Analysis for Prostate Cancer Aggressiveness-Assessment

Imon Banerjee, Lewis Hahn, Geoffrey Sonn, Richard Fan and Daniel Rubin


Using Deep Learning to Estimate Systolic and Diastolic volumes from CMR-images

Jeroen Burms, Jonas Degrave, Iryna Korshunova and Joni Dambre


Measuring Adverse Drug Effects on Multimorbity using Tractable Bayesian Networks

Jessa Bekker, Arjen Hommersom, Martijn Lappenschaar and Jesse Davis


An Adaptive filtering Testing Procedure for Repeated Effects

Jingshu Wang, Art Owen and Chiara Sabatti


Stratification of patient trajectories using covariate latent variable models

Kieran Campbell and Christopher Yau


Ranking Biomarkers Through Mutual Information

Konstantinos Sechidis, Emily Turner, Paul Metcalfe, James Weatherall and Gavin Brown


The Opioid Atlas

Kris Sankaran, Suzanne Tamang and Ami Bhatt


Modeling trajectories of mental health: challenges and opportunities

Lauren Erdman, Ekansh  Sharma, Eva Unternaehrer, Shantala H Dass, Anna Goldenberg, Michael Meaney, Michael Kobor, Sara Mostafavi, Helene Gaudreau and Rachel Edgar


Positive blood culture detection in time series data using a BiLSTM network

Leen De Baets, Joeri Ruyssinck, Thomas Peiffer, Johan Decruyenaere, Filip De Turck, Femke Ongenae and Tom Dhaene


Sparse Multivariate Gaussian Processes for Medical Time-Series Prediction

Li-Fang Cheng, Gregory Darnell, Corey Chivers, Michael Draugelis, Kai Li and Barbara Engelhardt


Phenotyping immune responses in asthma and respiratory infections -- A systems approach

Lijing Lin, Danielle Belgrave, Adnan Custovic and Magnus Rattray


Partially blind domain adaptation for age prediction from DNA methylation data

Lisa Handl, Adrin Jalali, Michael Scherer and Nico Pfeifer


Data driven techniques to optimise the management of septic shock

Matthieu Komorowski


A Markov Decision Process to suggest optimal treatment of severe

infections in intensive care

Matthieu Komorowski, Anthony Gordon, Leo Anthony Celi and Aldo Faisal


Supervised topic models for clinical interpretability

Michael Hughes, Melih Elibol, Thomas McCoy, Roy Perlis and Finale Doshi-Velez


Fast and Efficient Feature Engineering for Multi-Cohort Analysis of EHR Data

Michal Ozery-Flato, Chen Yanover, Assaf Gottlieb, Omer Weissbrod, Naama Parush Shear-Yashuv and Yaara Goldschmidt


On the Challenges of using Propensity Score Matching to study ICU patients

Miguel Paredes, Una-May O'Reilly and Erik Hemberg


Multi-task Learning in the Computerized Diagnosis of Breast Cancer on DCE-MRIs

Natalia Antropova, Benjamin Huynh and Maryellen Giger


Multi-task Learning for Predicting Health, Stress, and Happiness

Natasha Jaques, Sara Taylor, Ehimwenma Nosakhare, Akane Sano and Rosalind Picard


Deep Recurrent Models for Prediction of ICU Mortality and Sepsis

Nathan Hunt and Marzyeh Ghassemi



Nicolas Della Penna, Mark Reid and David Balduzzi


Towards multiple kernel principal component analysis for

integrative analysis of tumor samples.

Nora  Speicher and Nico Pfeifer


Neural Document Embeddings for Intensive Care Patient Mortality Prediction.

Paulina Grnarova, Florian Schmidt, Stephanie Hyland and Carsten Eickhoff


Learning what to look in chest X-rays with a recurrent visual attention model.

Petros-Pavlos Ypsilantis and Giovanni Montana


Identifying and Categorizing Anomalies in Retinal Imaging Data

Philipp Seeböck, Sebastian Waldstein, Sophie Klimscha, Bianca Gerendas, René Donner, Thomas Schlegl, Ursula Schmidt-Erfurth and Georg Langs


Learning from an expert in anesthesia.

Pierre Humbert, Julien Audiffren, Clément Dubost and Laurent Oudre


A Novel Classification Framework for Characterization of

Dysmorphologic Syndromes Using 3D Facial Topography.

Poay Hoon Lim, Jordan Bannister, Francois Bernier, Richard Spritz, Ophir Klein, Nick Mahasuwan, Sheri Riccardi, Jacinda Larson, David Aponte, Benedikt Hallgrimsson and Nils Forkert


Filter sharing: Efficient learning of parameters for volumetric convolutions.

Rahul Venkataramani, Sudhakar Prasad, Sheshadri Thiruvenkadam, Hariharan Ravishankar and Vivek Vaidya


MusculoSkeletal Modeling Using Kinect Data For Telerehabilitation

Rajat Das, Soumya Ranjan Tripathy, Kingshuk Chakravarty, Debatri Chatterjee, Aniruddha Sinha and Rupam Chaudhury

Diagnostic Prediction Using Discomfort Drawings

Cheng Zhang, Hedvig Kjellstrom and Bo C Bertilson


POSTER SESSION 3 (5:00 - 5:30)


Bayesian clustering identifies allergic response patterns

that are predictive of clinical outcomes

Rebecca Howard, Magnus Rattray and Panagiotis Papastamoulis


Multi-study factor model in dietary pattern analysis

Roberta de Vito


Sub-linear Privacy-preserving Search with Unsecured Server and Semi-honest Parties

Sadegh Riazi, Beidi Chen, Anshumali Shrivastava, Dan Wallach and Farinaz Koushanfar


A temporal model for multiple sclerosis course evolution

Samuele Fiorini, Andrea Tacchino, Giampaolo Brichetto, Alessandro Verri and Annalisa Barla


Variational Adversarial Deep Domain Adaptation for Health Care Time Series Analysis

Sanjay Purushotham, Wilka Carvalho and Yan Liu


Voxelwise nonlinear regression toolbox for neuroimage analysis: Application to aging andneurodegenerative disease modeling

Santi Puch, Asier Aduriz, Adrià Casamitjana, Veronica Vilaplana, Paula Petrone, Grégory Operto, Raffaele Cacciaglia, Stavros Skouras, Carles Falcon, Jose Luis Molinuevo and Juan Domingo Gispert


Clustering of Longitudinal Urine Toxicology Data  extended abstract

Sean Luo, Galen Xing, Jeff Goldsmith and Edward Nunes


EHR-based predictive models for adverse outcomes on the wards using partial least squares classification model.

Shirin Shahriari, André Gomes, José Almeida and Ana Azevedo


HealthAdvisor:Recommendation System for Wearable Technologies enabling Proactive HealthMonitoring

Shubhi Asthana, Ray Strong and Aly Megahed


Towards Wide Learning: Experiments in Healthcare.

Snehasis Banerjee, Tanushyam Chattopadhyay, Swagata Biswas, Rohan Banerjee, Anirban Dutta Choudhury, Arpan Pal and Utpal Garain


Combining Kernel and Model Based Learning for HIV Therapy Selection.

Sonali Parbhoo, Volker Roth and Finale Doshi-Velez


Multi-Organ Cancer Classification and Survival Analysis

Stefan Bauer, Nicolas Carion, Peter Schüffler, Joachim M  Buhmann, Peter Wild and Thomas Fuchs


Predicting Changes in Affective States using Neural Networks

Stina Lyck Cartsensen, Jens Madsen and Jan Larsen


Deep neural heart rate variability analysis

Tamas Madl


Learning Biomarkers for Alzheimer’s Disease from Shape Attributes of Brain Structures.

Tanya Glozman, Justin Solomon, Franco Pestilli and Leonidas Guibas


Transfer Learning Across Patient Variations with Hidden Parameter Markov Decision Processes.

Taylor Killian, Finale Doshi-Velez and George Konidaris


Generating Clinical Text from Dialogue.

Teppei Nakano


Quantifying Dose Response Relationships Between Physical Activity and Health Using Propensity Scores.

Tim Althoff, Rok Sosic, Jen Hicks, Abby King, Scott Delp and Jure Leskovec


Intra-day Activity Better Predicts Chronic Conditions

Tom Quisel, Luca Foschini and David Kale


A Noise-Filtering Approach for Cancer Drug Sensitivity Prediction.

Turki Turki and Zhi Wei


A Machine-Compiled Database of Genome-Wide Association Studies.

Volodymyr Kuleshov. Braden Hancock, Alexander Ratner, Christopher Re, Serafim Batzoglou and Michael Snyder


Diet2Vec:Multi-scale analysis of massive dietary data.

Wesley Tansey, Edward W Lowe and James Scott


Toward the Creation a Large Corpus of Synthetically-Identified Clinical Notes.

Willie Boag, Tristan Naumann and Peter Szolovits


Meta-regression trees: a tool to identify effective combinations of intervention components in meta-analysis.

Xinru Li, Elise Dusseldorp and Jacqueline Meulman


Learning to count and classify mosquitoes for the Sterile Insect Technique.

Yaniv Ovadia, Yoni Halpern, Dilip Krishnan, Josh Livni, Daniel Newburger, Ryan Poplin, Tiantian Zha and D. Sculley


Predictive Clinical Decision Support System with RNN Encoding and Tensor Decoding.

Yinchong Yang, Peter Fasching and Volker Tresp


Skin Cancer Detection and Tracking using Data Synthesis and Deep Learning

Yunzhu Li, Andre Esteva, Brett Kuprel, Rob Novoa, Justin Ko and Sebastian Thrun


Differential Data Augmentation Techniques for Medical Imaging Classification Tasks.

Zeshan Hussain, Francisco Gimenez, Darvin Yi and Daniel Rubin


Exploiting Convolutional Neural Network for Risk Prediction with Medical Feature Embedding.

Zhengping Che, Yu Cheng, Zhaonan Sun and Yan Liu 

Improving Hemoglobin A1c Prediction by Leveraging Participant Similarity 

Chia-Ying Lee, Amy McKenzie and David Bill