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人工智能医学 /Artificial intelligence in medicine

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人工智能医学 /Artificial intelligence in medicine

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作 者:SilvanaQuaglini 著

出 版 社:湖南文艺出版社

出版时间:2001-12-1

I S B N:9783540422945

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内容简介

This book constitutes the refereed proceedings of the Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making, AIMDM'99, held in Aalborg, Denmark, in June 1999.The 27 full papers and 19 short papers presented in the book together with four invited papers were selected from 90 submissions. The papers are organized in topical sections on guidelines and protocols; decision support systems, knowledge-based systems, and cooperative systems; model-based systems; neural nets and causal probabilistic networks; knowledge representation; temporal reasoning; machine learning; natural language processing; and image processing and computer aided design.

作者简介

目录

Mediated Agent Interaction
On Articulation and Localization - Some Sociotechnical Issues of Design, Implementation, and Evaluation of Knowledge Based Systems
Prototype Selection and Feature Subset Selection by Estimation of
Distribution Algorithms. A Case Study in the Survival of Cirrhotic
Patients Treated with TIPS
Detection of Infectious Outbreaks in Hospitals through Incremental
Clustering
Minig Data from a Knowledge Management Perspective: An Application to
Outcome Prediction in Patients with Resectable Hepatocellular Carcinoma
Discovering Associations in Clinical Data: Application to Search
for Prognostic Factors in Hodgkin's Disease
Visualisation of Multidimensional Data for Medical Decision Support
A Clustering-Based Constructive Induction Method and Its Application
to Rheumatoid Arthritis
Improving Identification of Difficult Small Classes by Balancing
Class Distribution
Credal Classification for Dementia Screening
Evaluation of Prognostic Factors and Prediction of Chronic Wound Healing
Rate by Machine Learning Tools :
Making Reliable Diagnoses with Machine Learning: A Case Study
A Classification-Tree Hybrid Method for Studying Prognostic Models in
Intensive Care
Combining Unsupervised and Supervised Machine Learning in Analysis of
the CHD Patient Database
Coronary Heart Disease Patient Models Based on
Inductive Machine Learning
Prediction of Protein Secondary Structures of All Types
Using New Hypersphere Machine Learning Method
ntegrating Different Methodologies for Insulin Therapy Support in Type
1 Diabetic Patients
Diagnosing Patient State in Intensive Care Patients Using the Intelligent
Ventilator (INVENT) System
A User Interface for Executing Asbru Plans
Improving HISYS1 with a Decision-Support System
Diagnosis of Iron-Deficiency Anemia in Hemodialyzed Patients through
Support Vector Machines Technique
A Visual Tool for a User-Friendly Artificial Neural Network Based Decision
Support System in Medicine
Modeling of Ventricular Repolarisation Time Series by Multi-layer Perceptrons
……
Author Index

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