Ameen Abu-Hanna
Evaluation of Prediction Models in Medicine

Lynda Tamine, Lorraine Goeuriot
Medical Information Retrieval

Philipp Cimiano, Laura Moss, Olivia Sanchez-Graillet, Basil Ell
Argumentation Technology in Medicine

1. Welcome
2. Daniele Di Mitri: Detecting Medical Simulation Errors with Machine Learning and Multimodal Data
3. Sara Garcia: Predict Nephrotoxicity Associated with Cisplatin-based Chemotherapy in Testicular Cancer Patients
4. Ana Herzog: Developing a Computer-based Battery of Tests for Assessing Dyslexia

Trip to Poznan Supercomputing
and Networking Center 

1. Yan Jia: Improving Medication Safety Using Machine Learning
2. Johanne Bakalara: Temporal Models of Care Sequences for the Exploration of  Medico-administrative Data

Anthony Chang: Common Misconceptions and Future Directions for AI in Medicine: A Physician-Data Scientist Perspective

1. Jeong Min Lee, Milos Hauskrecht: Recent Context-aware LSTM for Clinical Event Time-series Prediction (L)
2. Chiara Picardi, Ibrahim Habli: Perspectives on Assurance Case Development for Retinal Disease Diagnosis using Deep Learning (S)
3. Riccardo Belluzzo, Tomasz Grzywalski, Mateusz Piecuch, Marcin Szajek, Anna Bręborowicz, Anna Pastusiak, Honorata Hafke-Dys, Jędrzej Kociński: Fully Interactive Lungs Auscultation with AI Enabled Digital Stethoscope (S)
4. Francisco Luna-Perejon, Javier Civit-Masot, Isabel De Los Reyes Amaya-Rodriguez, Lourdes Duran-Lopez, Juan Pedro Dominguez-Morales, Anton Civit, Alejandro Linares-Barranco: An Automated Fall Detection System Using Recurrent Neural Networks (S)
5. Giovanna Nicora, Simone Marini, Ivan Limongelli, Ettore Rizzo, Stefano Montoli, Francesca Floriana Tricomi, Riccardo Bellazzi: A Semi-supervised Learning Approach for Pan-cancer Somatic Genomic Variant Classification (S)

1. Subhrajit Roy, Isabell Kiral-Kornek, Stefan Harrer: ChronoNet: A Deep Recurrent Neural Network for Abnormal EEG Identification (L)
2. Xiaoying Tan, Gerd Reis, Didier Stricker: Convolutional Recurrent Neural Network for Bubble Detection in a Portable Continuous Bladder Irrigation Monitor (L)
3. Rami Ben-Ari, Yoel Shoshan, Tal Tlusty: Mammogram Classification with Ordered Loss (L)
   Daniele Pala, John Holmes, José Pagán, Enea Parimbelli, Marica Teresa Rocca, Vittorio Casella, Riccardo Bellazzi: Agent-based Models and Spatial Enablement: A Simulation Tool to Improve Health and Wellbeing in Big Cities (S)
4. Camilo Andrés Cáceres Flórez, Joao Mauricio Rosario, Dario Amaya Hurtado: Towards Health 4.0: e-Hospital Proposal Based Industry 4.0 and Artificial Intelligence Concepts (S)

1. Martin Michalowski, Szymon Wilk, Wojtek Michalowski, Marc Carrier: MitPlan: A Planning Approach to Mitigating Concurrently Applied Clinical Practice Guidelines (L)
2. Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, François Petitjean, Lhassane Idoumghar, Pierre-Alain Muller: Automatic Alignment of Surgical Videos Using Kinematic Data (L)
3. Giovanna Nicora, Ivan Limongelli, Riccardo Cova, Matteo Giovanni Della Porta, Luca Malcovati, Mario Cazzola, Riccardo Bellazzi: A Rule-based Expert System for Automatic Implementation of Somatic Variant Clinical Interpretation Guidelines (S)
4. Paolo Terenziani, Antonella Andolina: Considering Temporal Preferences and Probabilities in Guideline Interaction Analysis (S)
5. Seyedsalim Malakouti, Milos Hauskrecht: Predicting Patient's Diagnoses and Diagnostic Categories from Clinical-events in EHR Data (S)
6. Maciej Piernik, Joanna Sołomiewicz, Arkadiusz Jachnik: Assessing the Effectiveness of Sequences of Treatments Using Sequential Patterns (S)
7. Jidapa Kraisangka, Marek J. Druzdzel, Lisa C. Lohmueller, Manreet K. Kanwar, James F. Antaki, Raymond L. Benza: A Bayesian Network vs. Cox’s Proportional Hazard Model of PAH Risk: A Comparison (L)
8. David Cuadrado, David Riaño, Josep Gómez, María Bodí, Gonzalo Sirgo, Federico Esteban, Rafael García, Alejandro Rodríguez: Pursuing Optimal Prediction of Discharge Time in ICUs with Machine Learning Methods (S)
9. Elisa Salvi, Enea Parimbelli, Lucia Sacchi, Silvana Quaglini, Erika Maggi, Lorry Duchoud, Gian Luca Armas, John De Almeida, Christian Simon: Towards the Economic Evaluation of Two Mini-Invasive Surgical Techniques for Head&neck Cancer: A Customizable Model for Different Populations (S)

1. Negar Safinianaini, Henrik Boström, Viktor Kaldo: Gated Hidden Markov Models for Early Prediction of Outcome of Internet-based Cognitive Behavioral Therapy (L)
2. Marcos Luiz de Paula Bueno, Arjen Hommersom, Peter Lucas, Joost Janzing: A Data-driven Exploration of Hypotheses on Disease Dynamics (L)
3. Agastya Silvina, Juliana Bowles, Peter Hall: On Predicting the Outcomes of Chemotherapy Treatments in Breast Cancer (L)
4. Harry Freitas da Cruz, Boris Pfahringer, Frederic Schneider, Alexander Meyer, Matthieu-P. Schapranow: External Validation of a "Black-Box" Clinical Predictive Model in Nephrology: Can Interpretability Approaches Help Illuminate Performance Differences? (L)

1. Emre Besler, Yearnchee Curtis Wang, Terence Chee-Hung Chan, Alan Varteres Sahakian: Classifying Small Volumes of Tissue for Real-Time Monitoring Radiofrequency Ablation (L)
2. Patrice C. Roy, William Van Woensel, Andrew Wilcox, Syed Sibte Raza Abidi: Mobile Indoor Localization with Bluetooth Beacons in a Pediatric Emergency Department Using Clustering, Rule-based Classification and High-level Heuristics (L)
3. Elisa Salvi, Silvia Panzarasa, Riccardo Bagarotti, Michela Picardi, Rosangela Boninsegna, Irma Sterpi, Massimo Corbo, Giordano Lanzola, Silvana Quaglini, Lucia Sacchi: NONCADO: A System to Prevent Falls by Encouraging Healthy Habits in Elderly People (S)
4. Yan Zeng, Paolo Fraccaro, Niels Peek: The Minimum Sampling Rate and Sampling Duration When Applying Geolocation Data Technology to Human Activity Monitoring (S)

Ivana Bertoletti: AI in Healthcare: Ethical and Privacy Challenges

1. Syed Sibte Raza Abidi, Jaber Rad, Ashraf Abusharekh, Patrice C. Roy, Willian Van Woensel, Samina Abidi, Calvino Cheng, Bryan Crocker, Manal Elnenaei: AI-Driven Pathology Laboratory Utilization Management via Data- and Knowledge-Based Analytics (L)
2. Vincent Menger, Marco Spruit, Wouter van der Klift, Floor Scheepers: Using Cluster Ensembles to Identify Psychiatric Patient Subgroups (L)
3. Anita Valmarska, Dragana Miljkovic, Marko Robnik-Sikonja, Nada Lavrač: Connection Between the Parkinson's Disease Subtypes and Patients' Symptoms Progression (S)
4. Antonio Lopez Martinez-Carrasco, Jose M. Juarez, Manuel Campos, Antonio Morales, Francisco Palacios, Lucia Lopez-Rodriguez: Interpretable Patient Subgrouping Using Trace-based Clustering (S)
5. Tsanta Randriatsitohaina, Thierry Hamon: Extracting Food-drug Interactions from Scientific Literature: Tackling Unspecified Relation (S)
6. Sandhya Prabhakaran, Julia Vogt: Bayesian Clustering For HIV1 Protease Inhibitor Contact Maps (S)
7. Gilles Vandewiele, Isabelle Dehaene, Olivier Janssens, Femke Ongenae, Femke De Backere, Filip De Turck, Kristien Roelens, Sofie Van Hoecke, Thomas Demeester: Time-to-birth Prediction Models and the Influence of Expert Opinions (S)
8. Mariana Neves, William Marsh: Modelling the Impact of AI for Clinical Decision Support (S)
9. Natalia Viani, Rashmi Patel, Robert Stewart, Sumithra Velupillai: Generating Positive Psychosis Symptom Keywords from Electronic Health Records (S)
10. Vaishnavi Ameya Murukutla, Elie Cattan, Olivier Palombi, Rémi Ronfard: Text-to-Movie Authoring of Anatomy Lessons (S)

1. Christopher Bartlett, Stephen Glatt, Isabelle Bichindaritz: Machine Learning and Feature Selection for the Classification of Mental Disorders from Methylation Data (L)
2. Chirath Hettiarachchi, Charith Chitraranjan: A Machine Learning Approach to Predict Diabetes Using Short Recorded Photoplethysmography & Physiological Characteristics (S)
3. Josephine French, Cong Chen, Katherine Henson, Brian Shand, Patrick Ferris, Joshua Pencheon, Sally Vernon, Meena Rafiq, David Howe, Georgios Lyratzopoulos, Jem Rashbass: Identification of Patient Prescribing Predicting Cancer Diagnosis Using Boosted Decision Trees (S)
4. Carlos González, Pedro Bibiloni, Manuel González-Hidalgo, Arnau Mir, Sebastià Rubí: Automatic Image-Derived Estimation of the Arterial Whole-Blood Input Function from Dynamic Cerebral PET with 18F-Choline (L)
5. Md. Abu Sayed, Sajib Saha, G M Atiqur Rahaman, Tanmai K. Ghosh, Yogesan Kanagasingam: A Semi-supervised Approach to Segment Retinal Blood Vessels in Color Fundus Photographs (S)
6. Gilles Vandewiele, Isabelle Dehaene, Olivier Janssens, Femke Ongenae, Femke De Backere, Filip De Turck, Kristien Roelens, Sofie Van Hoecke, Thomas Demeester: A Critical Look at Studies Applying Over-sampling on the TPEHGDB Dataset (L)
7. Ying-Feng Hsu, Makiko Ito, Takumi Maruyama, Morito Matsuoka, Nicolas Jung, Yuki Matsumoto, Daisuke Motooka, Shota Nakamura: Deep Learning Approach for Pathogen Detection through Shotgun Metagenomics Sequence Classification (S)
8. Martin Stražar, Lan Žagar, Jaka Kokošar, Vesna Tanko, Pavlin Poličar, Aleš Erjavec, Ajda Pretnar, Anze Starič, Vilas Menon, Rui Chen, Gad Shaulsky, Andrew Lemire, Anup Parikh, Blaž Zupan: Single-Cell Data Analytics in scOrange (S)
9. Ananya Rajagopalan, Marcus Vollmer: Rapid Detection of Heart Rate Fragmentation and Cardiac Arrhythmias: Cycle-by-Cycle rr Analysis, Statistical Analysis, Supervised Machine Learning Model and Novel Insights (S)

1. Linda Lapp, Matt-Mouley Bouamrane, Kimberley Kavanagh, Marc Roper, David Young, Stefan Schraag: Evaluation of Random Forest and Ensemble Methods at Predicting Complications Following Cardiac Surgery (L)
2. Matteo Mantovani, Milos Hauskrecht, Carlo Combi: Mining Compact Predictive Pattern Sets Using Classification Model (L)
3. Arianna Dagliati, Nophar Geifman, Niels Peek, John Holmes, Lucia Sacchi, Seyed Erfan Sajjadi, Allan Tucker: Inferring Temporal Phenotypes with Topological Data Analysis and Pseudo Time-Series (L)
4. Luca Corinzia, Jesse Provost, Alessandro Candreva, Maurizio Tamarasso, Francesco Maisano, Joachim M. Buhmann: Unsupervised Mitral Valve Segmentation in Echocardiography with Neural Network Matrix Factorization (L)
5. Teodora Matić, Somayeh Aghanavesi, Mevludin Memedi, Dag Nyholm, Filip Bergquist, Vida Groznik, Jure Zabkar, Aleksander Sadikov: Unsupervised Learning from Motion Sensor Data to Assess the Condition of Patients with Parkinson's Disease (S)

Wojtek Michalowski: Multi-morbid and Poorly Motivated Patient: How to Arrive at a Right Therapy and Help with Adhering to It

1. Mar Marcos, Cristina Campos Sancho, Begoña Martínez-Salvado: A Practical Exercise on Re-engineering Clinical Guideline Models Using Different Representation Language (L)
2. Liu Shen, Hongyu Kang, Si Zheng, Meng Wu, Li Hou, Jiao Li: A Knowledge Representation Model for Clinical Pharmacology data integration: a Case Study in NSCLC Pharmacology (S)
3. Xiaoshuo Huang, Lin Yang, Jiao Li: A Knowledge Representation Model for Health Information Standards: A Case Study of HL7 Message Type (S)
4. Giorgio Leonardi, Stefania Montani, Manuel Striani: Deep Learning for Haemodialysis Time Series Classification (L)

1. Mor Peleg, Alexandra Kogan, Samson Tu: A Methodology for Goal-oriented Guideline Modeling in PROforma and its Preliminary Evaluation (L)
2. Alessio Bottrighi, Gianpaolo Molino, Luca Piovesan, Paolo Terenziani: GLARE-Edu: Exploiting Computer-Interpretable Guidelines in Education (S)
3. Ewelina Gowin, Jerzy Błaszczyński, Roman Slowinski, Jacek Wysocki Wysocki, Danuta Januszkiewicz-Lewandowska: Differential Diagnosis of Bacterial and Viral Meningitis Using Dominance-Based Rough Set Approach (L)
4. Clemens Gangl, Jan Maly, Martin Lackner, Stefan Woltran: Aggregating Expert Opinions in Support of Medical Diagnostic Decision-Making (S)

1. Mohammed Sayed, David Riaño: Modelling ICU Patients to Improve Care Requirements and Outcome Prediction of Acute Respiratory Distress Syndrome (L)
2. Alessio Bottrighi, Giorgio Leonardi, Stefania Montani, Paolo Terenziani: Knowledge-based Abstraction of Medical Process Models (S)
3. Lientje Maas, Adriaan Kisjes, Iman Hashemi, Floris Heijmans, Fabiano Dalpiaz, Sandra Van Dulmen, Sjaak Brinkkemper: Automated Medical Reporting: From Multimodal Inputs to Medical Reports with Knowledge Graphs (S)

Marcin Grzegorzek: Human-centred Pattern Recognition for Assistive Health Technologies

1. Olga Kamińska, Katarzyna Kaczmarek-Majer, Karol Opara, Wit Jakuczun, Monika Dominiak, Anna Antosik, Łukasz Święcicki, Olgierd Hryniewicz: Self Organizing Maps Using Acoustic Features for Prediction of State Change in Bipolar Disorder
2. Alexander Galozy, Slawomir Nowaczyk, Anita Sant'Anna: Towards Understanding ICU Treatments using Patient Health Trajectories
3. Erica Ramirez, Markus Wimmer, Martin Atzmueller: Interpretable Anomaly Detection and Classification of Multivariate Time Series for Transparent Human Gait Analysis

1. Leon Kopitar, Leona Cilar, Primoz Kocbek, Gregor Stiglic: Local vs. Global Interpretability of Machine Learning Models in Type 2 Diabetes Mellitus Screening
2. Bernardo Cánovas Segura, Antonio Morales, Antonio López Martínez-Carrasco, Manuel Campos, Jose M. Juarez, Lucía López-Rodríguez, Francisco Palacios: Exploring Antimicrobial Resistance Prediction Using Post-hoc Interpretable Methods
3. Katarzyna Kobylińska, Tomasz Mikołajczyk, Mariusz Adamek, Tadeusz Orłowski, Przemysław Biecek: Explainable Machine Learning for Modeling of Early Postoperative Mortality in Lung Cancer

1. Keyuan Jiang, Tingyu Chen, Liyuan Huang, Ricardo Calix, Gordon Bernard, Ravish Gupta: An Explainable Approach of Inferring Potential Medication Effects from Social Media Data
2. Xuwen Wang, Yu Zhang, Zhen Guo, Jiao Li: A Computational Framework Towards Medical Image Explanation