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ORCID17th AIME 2019: Poznan, Poland
- David Riaño, Szymon Wilk, Annette ten Teije
:
Artificial Intelligence in Medicine - 17th Conference on Artificial Intelligence in Medicine, AIME 2019, Poznan, Poland, June 26-29, 2019, Proceedings. Lecture Notes in Computer Science 11526, Springer 2019, ISBN 978-3-030-21641-2
Invited Speakers
- Anthony Chang:
Common Misconceptions and Future Directions for AI in Medicine: A Physician-Data Scientist Perspective. 3-6 - Ivana Bartoletti:
AI in Healthcare: Ethical and Privacy Challenges. 7-10
Deep Learning
- Jeongmin Lee, Milos Hauskrecht:
Recent Context-Aware LSTM for Clinical Event Time-Series Prediction. 13-23 - 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. 24-30 - Tomasz Grzywalski, Riccardo Belluzzo, Mateusz Piecuch, Marcin Szajek, Anna Breborowicz, Anna Pastusiak, Honorata Hafke-Dys, Jedrzej Kocinski:
Fully Interactive Lungs Auscultation with AI Enabled Digital Stethoscope. 31-35 - Francisco Luna-Perejón, Javier Civit-Masot, Isabel Amaya-Rodriguez, Lourdes Duran-Lopez, Juan Pedro Dominguez-Morales, Antón Civit Balcells, Alejandro Linares-Barranco:
An Automated Fall Detection System Using Recurrent Neural Networks. 36-41 - 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. 42-46 - Subhrajit Roy, Isabell Kiral-Kornek, Stefan Harrer:
ChronoNet: A Deep Recurrent Neural Network for Abnormal EEG Identification. 47-56 - Xiaoying Tan, Gerd Reis, Didier Stricker:
Convolutional Recurrent Neural Network for Bubble Detection in a Portable Continuous Bladder Irrigation Monitor. 57-66 - Rami Ben-Ari, Yoel Shoshan, Tal Tlusty:
Mammogram Classification with Ordered Loss. 67-76
Simulation
- Daniele Pala, John H. 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. 79-83 - Camilo Cáceres, João Maurício Rosário, Dario Amaya:
Towards Health 4.0: e-Hospital Proposal Based Industry 4.0 and Artificial Intelligence Concepts. 84-89
Knowledge Representation
- Martin Michalowski, Szymon Wilk, Wojtek Michalowski, Marc Carrier:
MitPlan: A Planning Approach to Mitigating Concurrently Applied Clinical Practice Guidelines. 93-103 - Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, François Petitjean, Lhassane Idoumghar, Pierre-Alain Muller:
Automatic Alignment of Surgical Videos Using Kinematic Data. 104-113 - 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. 114-119 - Paolo Terenziani, Antonella Andolina:
Considering Temporal Preferences and Probabilities in Guideline Interaction Analysis. 120-124 - Seyedsalim Malakouti, Milos Hauskrecht:
Predicting Patient's Diagnoses and Diagnostic Categories from Clinical-Events in EHR Data. 125-130 - Maciej Piernik, Joanna Solomiewicz, Arkadiusz Jachnik:
Assessing the Effectiveness of Sequences of Treatments Using Sequential Patterns. 131-135
Probabilistic Models
- Jidapa Kraisangka, Marek J. Druzdzel, Lisa C. Lohmueller, Manreet K. Kanwar, James F. Antaki, Raymond L. Benza:
Bayesian Network vs. Cox's Proportional Hazard Model of PAH Risk: A Comparison. 139-149 - 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. 150-154 - 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. 155-159 - Negar Safinianaini, Henrik Boström, Viktor Kaldo:
Gated Hidden Markov Models for Early Prediction of Outcome of Internet-Based Cognitive Behavioral Therapy. 160-169 - Marcos L. P. Bueno, Arjen Hommersom, Peter J. F. Lucas, Joost G. E. Janzing:
A Data-Driven Exploration of Hypotheses on Disease Dynamics. 170-179 - Agastya Silvina, Juliana Bowles, Peter S. Hall:
On Predicting the Outcomes of Chemotherapy Treatments in Breast Cancer. 180-190 - 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 Methods Help Illuminate Performance Differences? 191-201
Behavior Monitoring
- Emre Besler, Yearnchee Curtis Wang, Terence Chan, Alan Varteres Sahakian:
Classifying Small Volumes of Tissue for Real-Time Monitoring Radiofrequency Ablation. 205-215 - 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. 216-226 - 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. 227-232 - Yan Zheng, Paolo Fraccaro, Niels Peek:
The Minimum Sampling Rate and Sampling Duration When Applying Geolocation Data Technology to Human Activity Monitoring. 233-238
Clustering, Natural Language Processing, and Decision Support
- Syed Sibte Raza Abidi, Jaber Rad, Ashraf Abusharekh, Patrice C. Roy, William Van Woensel, Samina Raza Abidi, Calvino Cheng, Bryan Crocker, Manal Elnenaei:
AI-Driven Pathology Laboratory Utilization Management via Data- and Knowledge-Based Analytics. 241-251 - Vincent Jorn Menger, Marco Spruit, Wouter van der Klift, Floor Scheepers:
Using Cluster Ensembles to Identify Psychiatric Patient Subgroups. 252-262 - Anita Valmarska, Dragana Miljkovic, Marko Robnik-Sikonja, Nada Lavrac:
Connection Between the Parkinson's Disease Subtypes and Patients' Symptoms Progression. 263-268 - Antonio López Martínez-Carrasco, Jose M. Juarez, Manuel Campos, Antonio Morales Nicolás, Francisco Palacios, Lucía López-Rodríguez:
Interpretable Patient Subgrouping Using Trace-Based Clustering. 269-274 - Tsanta Randriatsitohaina, Thierry Hamon:
Extracting Food-Drug Interactions from Scientific Literature: Tackling Unspecified Relation. 275-280 - Sandhya Prabhakaran, Julia E. Vogt:
Bayesian Clustering for HIV1 Protease Inhibitor Contact Maps. 281-285 - 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. 286-291 - Mariana R. Neves, D. William R. Marsh:
Modelling the Impact of AI for Clinical Decision Support. 292-297 - Natalia Viani, Rashmi Patel, Robert Stewart, Sumithra Velupillai:
Generating Positive Psychosis Symptom Keywords from Electronic Health Records. 298-303 - Vaishnavi Ameya Murukutla, Elie Cattan, Olivier Palombi, Rémi Ronfard:
Text-to-Movie Authoring of Anatomy Lessons. 304-308
Feature Selection
- Christopher L. Bartlett, Stephen J. Glatt, Isabelle Bichindaritz:
Machine Learning and Feature Selection for the Classification of Mental Disorders from Methylation Data. 311-321 - Chirath Hettiarachchi, Charith Chitraranjan:
A Machine Learning Approach to Predict Diabetes Using Short Recorded Photoplethysmography and Physiological Characteristics. 322-327 - Josephine French, Cong Chen, Katherine Henson, Brian Shand, Patrick Ferris, Josh Pencheon, Sally Vernon, Meena Rafiq, David Howe, Georgios Lyratzopoulos, Jem Rashbass:
Identification of Patient Prescribing Predicting Cancer Diagnosis Using Boosted Decision Trees. 328-333
Image Processing
- 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 ^18 F-Choline. 337-346 - 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. 347-351
General Machine Learning
- 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. 355-364 - Chiara Picardi, Ibrahim Habli:
Perspectives on Assurance Case Development for Retinal Disease Diagnosis Using Deep Learning. 365-370 - Ananya Rajagopalan, Marcus Vollmer:
Rapid Detection of Heart Rate Fragmentation and Cardiac Arrhythmias: Cycle-by-Cycle rr Analysis, Supervised Machine Learning Model and Novel Insights. 371-375 - 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. 376-385 - Matteo Mantovani, Carlo Combi, Milos Hauskrecht:
Mining Compact Predictive Pattern Sets Using Classification Model. 386-396
Unsupervised Learning
- Arianna Dagliati, Nophar Geifman, Niels Peek, John H. Holmes, Lucia Sacchi, Seyed Erfan Sajjadi, Allan Tucker:
Inferring Temporal Phenotypes with Topological Data Analysis and Pseudo Time-Series. 399-409 - Luca Corinzia, Jesse Provost, Alessandro Candreva, Maurizio Tamarasso, Francesco Maisano, Joachim M. Buhmann:
Unsupervised Mitral Valve Segmentation in Echocardiography with Neural Network Matrix Factorization. 410-419 - Teodora Matic, 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. 420-424
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