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 /

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 Syst...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Marcos, Mar (Editor, http://id.loc.gov/vocabulary/relators/edt), Juarez, Jose M. (Editor, http://id.loc.gov/vocabulary/relators/edt), Lenz, Richard (Editor, http://id.loc.gov/vocabulary/relators/edt), Nalepa, Grzegorz J. (Editor, http://id.loc.gov/vocabulary/relators/edt), Nowaczyk, Slawomir (Editor, http://id.loc.gov/vocabulary/relators/edt), Peleg, Mor (Editor, http://id.loc.gov/vocabulary/relators/edt), Stefanowski, Jerzy (Editor, http://id.loc.gov/vocabulary/relators/edt), Stiglic, Gregor (Editor, http://id.loc.gov/vocabulary/relators/edt)
Format: Electronic eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
Edition:1st ed. 2019.
Series:Lecture Notes in Artificial Intelligence ; 11979
Subjects:
Online Access:Full Text via HEAL-Link
Table of Contents:
  • 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. .