KR4HC/ProHealth/TEAAM@AIME

Publications

2019

Giorgio Leonardi, Stefania Montani, Manuel Striani
Deep Learning for Haemodialysis Time Series Classification. KR4HC/ProHealth/TEAAM@AIME (2019)
Xuwen Wang, Yu Zhang, Zhen Guo, Jiao Li
A Computational Framework Towards Medical Image Explanation. KR4HC/ProHealth/TEAAM@AIME (2019)
Ewelina Gowin, Jerzy Blaszczynski, Roman Slowinski, Jacek Wysocki, Danuta Januszkiewicz-Lewandowska
Differential Diagnosis of Bacterial and Viral Meningitis Using Dominance-Based Rough Set Approach. KR4HC/ProHealth/TEAAM@AIME (2019)
Keyuan Jiang, Tingyu Chen, Liyuan Huang, Ravish Gupta, Ricardo A. Calix, Gordon R. Bernard
An Explainable Approach of Inferring Potential Medication Effects from Social Media Data. KR4HC/ProHealth/TEAAM@AIME (2019)
Mohammed Sayed, David Riaño
Modelling ICU Patients to Improve Care Requirements and Outcome Prediction of Acute Respiratory Distress Syndrome: A Supervised Learning Approach. KR4HC/ProHealth/TEAAM@AIME (2019)
Alexander Galozy, Slawomir Nowaczyk, Anita Pinheiro Sant'Anna
Towards Understanding ICU Treatments Using Patient Health Trajectories. KR4HC/ProHealth/TEAAM@AIME (2019)
Leon Kopitar, Leona Cilar, Primoz Kocbek, Gregor Stiglic
Local vs. Global Interpretability of Machine Learning Models in Type 2 Diabetes Mellitus Screening. KR4HC/ProHealth/TEAAM@AIME (2019)
Mor Peleg, Alexandra Kogan, Samson W. Tu
A Method for Goal-Oriented Guideline Modeling in PROforma and Its Preliminary Evaluation. KR4HC/ProHealth/TEAAM@AIME (2019)
Bernardo Cánovas-Segura, Antonio Morales Nicolás, Antonio López Martínez-Carrasco, Manuel Campos, Jose M. Juarez, Lucía López-Rodríguez, Francisco Palacios
Exploring Antimicrobial Resistance Prediction Using Post-hoc Interpretable Methods. KR4HC/ProHealth/TEAAM@AIME (2019)
Katarzyna Kobylinska, Tomasz Mikolajczyk, Mariusz Adamek, Tadeusz Orlowski, Przemyslaw Biecek
Explainable Machine Learning for Modeling of Early Postoperative Mortality in Lung Cancer. KR4HC/ProHealth/TEAAM@AIME (2019)
Olga Kaminska, Katarzyna Kaczmarek-Majer, Karol R. Opara, Wit Jakuczun, Monika Dominiak, Anna Antosik-Wójcinska, Lukasz Swiecicki, Olgierd Hryniewicz
Self-organizing Maps Using Acoustic Features for Prediction of State Change in Bipolar Disorder. KR4HC/ProHealth/TEAAM@AIME (2019)
Erica Ramirez, Markus Wimmer, Martin Atzmueller
A Computational Framework for Interpretable Anomaly Detection and Classification of Multivariate Time Series with Application to Human Gait Data Analysis. KR4HC/ProHealth/TEAAM@AIME (2019)
Mar Marcos, Cristina Campos, Begoña Martínez-Salvador
A Practical Exercise on Re-engineering Clinical Guideline Models Using Different Representation Languages. KR4HC/ProHealth/TEAAM@AIME (2019)

volume 11979, 2019

Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems - AIME 2019 International Workshops, KR4HC/ProHealth and TEAAM, Poznan, Poland, June 26-29, 2019, Revised Selected Papers KR4HC/ProHealth/TEAAM@AIME 11979 (2019)