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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 / edited by Mar Marcos, Jose M. Juarez, Richard Lenz, Grzegorz J. Nalepa, Slawomir Nowaczyk, Mor Peleg, Jerzy Stefanowski, Gregor Stiglic.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Lecture notes in computer science. Lecture notes in artificial intelligence 2945-9141 ; 11979
- Lecture Notes in Artificial Intelligence, 2945-9141 ; 11979
- Language:
- English
- Subjects (All):
- Artificial intelligence.
- Computer vision.
- Computer engineering.
- Computer networks.
- Education-Data processing.
- Application software.
- Artificial Intelligence.
- Computer Vision.
- Computer Engineering and Networks.
- Computer Communication Networks.
- Computers and Education.
- Computer and Information Systems Applications.
- Local Subjects:
- Artificial Intelligence.
- Computer Vision.
- Computer Engineering and Networks.
- Computer Communication Networks.
- Computers and Education.
- Computer and Information Systems Applications.
- Physical Description:
- 1 online resource (XII, 175 pages) : 56 illustrations, 42 illustrations in color.
- Edition:
- 1st ed. 2019.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2019.
- System Details:
- text file PDF
- Summary:
- 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.
- 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. .
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-37446-4
- 9783030374464
- Access Restriction:
- Restricted for use by site license.
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