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
tarafından
Marcos, Mar. editor. (orcid)0000-0001-9672-4190
Başlık
:
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
Yazar
:
Marcos, Mar. editor. (orcid)0000-0001-9672-4190
ISBN
:
9783030374464
Edisyon
:
1st ed. 2019.
Fiziksel Niteleme
:
XII, 175 p. 56 illus., 42 illus. in color. online resource.
Seri
:
Lecture Notes in Artificial Intelligence ; 11979
İçindekiler
:
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. .
Özet
:
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.
Konu Başlığı
:
Artificial intelligence.
Optical data processing.
Computer organization.
Computers.
Education—Data processing.
Application software.
Artificial Intelligence. https://scigraph.springernature.com/ontologies/product-market-codes/I21000
Image Processing and Computer Vision. https://scigraph.springernature.com/ontologies/product-market-codes/I22021
Computer Systems Organization and Communication Networks. https://scigraph.springernature.com/ontologies/product-market-codes/I13006
Information Systems and Communication Service. https://scigraph.springernature.com/ontologies/product-market-codes/I18008
Computers and Education. https://scigraph.springernature.com/ontologies/product-market-codes/I24032
Computer Applications. https://scigraph.springernature.com/ontologies/product-market-codes/I23001
Yazar Ek Girişi
:
Marcos, Mar.
Juarez, Jose M.
Lenz, Richard.
Nalepa, Grzegorz J.
Nowaczyk, Slawomir.
Peleg, Mor.
Stefanowski, Jerzy.
Stiglic, Gregor.
Ek Kurum Yazar
:
SpringerLink (Online service)
Elektronik Erişim
:
Materyal Türü | Barkod | Yer Numarası | Durumu/İade Tarihi |
---|
Electronic Book | 428567-1001 | Q334 -342 | Springer E-Book Collection |