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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 /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems/ edited by Mar Marcos, Jose M. Juarez, Richard Lenz, Grzegorz J. Nalepa, Slawomir Nowaczyk, Mor Peleg, Jerzy Stefanowski, Gregor Stiglic.
其他題名:	AIME 2019 International Workshops, KR4HC/ProHealth and TEAAM, Poznan, Poland, June 26–29, 2019, Revised Selected Papers /
其他作者:	Marcos, Mar.
面頁冊數:	XII, 175 p. 56 illus., 42 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Artificial intelligence. -
電子資源:	https://doi.org/10.1007/978-3-030-37446-4
ISBN:	9783030374464

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 /
Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable SystemsAIME 2019 International Workshops, KR4HC/ProHealth and TEAAM, Poznan, Poland, June 26–29, 2019, Revised Selected Papers /[electronic resource] :edited by Mar Marcos, Jose M. Juarez, Richard Lenz, Grzegorz J. Nalepa, Slawomir Nowaczyk, Mor Peleg, Jerzy Stefanowski, Gregor Stiglic. - 1st ed. 2019. - XII, 175 p. 56 illus., 42 illus. in color.online resource. - Lecture Notes in Artificial Intelligence ;11979. - Lecture Notes in Artificial Intelligence ;9285.

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. .

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.

ISBN: 9783030374464

Standard No.: 10.1007/978-3-030-37446-4doiSubjects--Topical Terms:

559380
Artificial intelligence.

LC Class. No.: Q334-342

Dewey Class. No.: 006.3

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 /
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