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DISPONIBILITÀ IMMEDIATA
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Libro
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Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems
marcos mar (curatore); juarez jose m. (curatore); lenz richard (curatore); nalepa grzegorz j. (curatore); nowaczyk slawomir (curatore); peleg mor (curatore); stefanowski jerzy (curatore); stiglic gregor (curatore)
54,98 €
52,23 €
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TRAMA
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.SOMMARIO
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.ALTRE INFORMAZIONI
- Condizione: Nuovo
- ISBN: 9783030374457
- Collana: Lecture Notes in Computer Science
- Dimensioni: 235 x 155 mm
- Formato: Brossura
- Illustration Notes: XII, 175 p. 56 illus., 42 illus. in color.
- Pagine Arabe: 175
- Pagine Romane: xii