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Artificial intelligence in medicine ...

Conference on Artificial Intelligence in Medicine (2005-) (2019 :)

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Artificial intelligence in medicine = knowledge repsentation 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-電子資源 : Monograph/item
正題名/作者:	Artificial intelligence in medicine/ edited by Mar Marcos ... [et al.].
其他題名:	knowledge repsentation and transparent and explainable systems : AIME 2019 International Workshops, KR4HC/ProHealth and TEAAM, Poznan, Poland, June 26-29, 2019 : revised selected papers /
其他題名:	AIME 2019
其他作者:	Marcos, Mar.
團體作者:	Conference on Artificial Intelligence in Medicine (2005-)
出版者:	Cham :Springer International Publishing : : 2019.,
面頁冊數:	xii, 175 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer Nature eBook
標題:	Medical informatics - Congresses. -
電子資源:	https://doi.org/10.1007/978-3-030-37446-4
ISBN:	9783030374464

Artificial intelligence in medicine = knowledge repsentation 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 medicineknowledge repsentation and transparent and explainable systems : AIME 2019 International Workshops, KR4HC/ProHealth and TEAAM, Poznan, Poland, June 26-29, 2019 : revised selected papers /[electronic resource] :AIME 2019edited by Mar Marcos ... [et al.]. - Cham :Springer International Publishing :2019. - xii, 175 p. :ill., digital ;24 cm. - Lecture notes in computer science,119790302-9743 ;. - Lecture notes in computer science ;11979..

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:

590642
Medical informatics
--Congresses.

LC Class. No.: R858.A2 / C66 2019

Dewey Class. No.: 006.3

Artificial intelligence in medicine = knowledge repsentation 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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