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

Contributor:

Marcos, Mar, editor.

Juarez, Jose M., editor.

Lenz, Rick, editor.

Nalepa, Grzegorz J., editor.

Nowaczyk, Slawomir, editor.

Peleg, Mor, editor.

Stefanowski, Jerzy, editor.

Štiglic, Gregor, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 11979.

Lecture Notes in Artificial Intelligence ; 11979

Language:

English

Subjects (All):

Artificial intelligence.

Optical data processing.

Computer organization.

Computers.

Education--Data processing.

Education.

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.

Local Subjects:

Artificial Intelligence.

Image Processing and Computer Vision.

Computer Systems Organization and Communication Networks.

Information Systems and Communication Service.

Computers and Education.

Computer Applications.

Physical Description:

1 online resource (XII, 175 pages) : 56 illustrations, 42 illustrations in color.

Edition:

First edition 2019.

Contained In:

Springer eBooks

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.