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 /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Marcos, Mar (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Juarez, Jose M. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Lenz, Richard (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Nalepa, Grzegorz J. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Nowaczyk, Slawomir (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Peleg, Mor (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Stefanowski, Jerzy (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Stiglic, Gregor (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Σειρά: Lecture Notes in Artificial Intelligence ; 11979
• Θέματα: Artificial intelligence.; Optical data processing.; Computer organization.; Computers.; Education-Data processing.; Application software.; Artificial Intelligence.; Image Processing and Computer Vision.; Computer Systems Organization and Communication Networks.; Information Systems and Communication Service.; Computers and Education.; Computer Applications.

 This book constitutes revised selected papers from the AIME 2019 workshops KR4HC/ProHealth 2019, the Workshop on Knowledge Representation for Health Care and Process-Oriented Information Systems in Health Care, and TEAAM 2019, the Workshop on Transparent, Explainable and Affective AI in Medical Systems. The volume contains 5 full papers from KR4HC/ProHealth, which were selected out of 13 submissions. For TEAAM 8 papers out of 10 submissions were accepted for publication. 

 KR4HC/ProHealth - Joint Workshop on Knowledge Representation for Health Care and Process-Oriented Information Systems in Health Care -- A practical exercise on re-engineering clinical guideline models using different representation languages -- A method for goal-oriented guideline modeling in PROforma and ist preliminary evaluation -- Differential diagnosis of bacterial and viral meningitis using Dominance-Based Rough Set Approach -- Modelling ICU Patients to Improve Care Requirements and Outcome Prediction of Acute Respiratory Distress Syndrome: A Supervised Learning Approach -- Deep learning for haemodialysis time series classification -- TEAAM - Workshop on Transparent, Explainable and Affective AI in Medical Systems -- Towards Understanding ICU Treatments using Patient Health Trajectories -- An Explainable Approach of Inferring Potential Medication Effects from Social Media Data -- Exploring antimicrobial resistance prediction using post-hoc interpretable methods -- Local vs. Global Interpretability of Machine Learning Models in Type 2 Diabetes Mellitus Screening -- A Computational Framework towards Medical Image Explanation -- A Computational Framework for Interpretable Anomaly Detection and Classification of Multivariate Time Series with Application to Human Gait Data Analysis -- Self-organizing maps using acoustic features for prediction of state change in bipolar disorder -- Explainable machine learning for modeling of early postoperative mortality in lung cancer. .