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...
Corporate Author: | |
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Other Authors: | , , , , , , , |
Format: | Electronic eBook |
Language: | English |
Published: |
Cham :
Springer International Publishing : Imprint: Springer,
2019.
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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. .