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Medical Data Analysis [electronic resource] : 4th International Symposium, ISMDA 2003, Berlin, Germany, October 9-10, 2003, Proceedings /

Contributor(s): Material type: TextTextSeries: Lecture Notes in Computer Science ; 2868Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2003Edition: 1st ed. 2003Description: VIII, 132 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540396192
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 610.72 23
LOC classification:
  • R850.A1-854
  • QH315-320
Online resources:
Contents:
Medical Models and Learning -- Possibility-Probability Relation in Medical Models -- How Exactly Do We Know Inheritance Parameters? -- Tuning of Diagnosis Support Rules through Visualizing Data Transformations -- Inductive Learning of Simple Diagnostic Scores -- Integration of Intelligent Analysis Methods into Medical Data Bases -- A Virtual Approach to Integrating Biomedical Databases and Terminologies -- Data Mining with Meva in MEDLINE -- Medical Signal and Image Analysis -- Isobologram Analysis in MATLAB for Combined Effects of Two Agents in Dose-Response Experiments -- Towards an Improved On-line Algorithm to Estimate the Fetal Heart Rate from Ultrasound Data -- Health Monitoring by an Image Interpretation System – A System for Airborne Fungi Identification -- Quantification and Characterization of Pulmonary Emphysema in Multislice-CT -- Interactive Visualization of Diagnostic Data from Cardiac Images Using 3D Glyphs -- Applications of Medical Diagnostic Support Systems -- Predicting Influenza Waves with Health Insurance Data -- Fuzzy Inference Systems for Multistage Diagnosis of Acute Renal Failure in Children -- Data Imbalance in Surveillance of Nosocomial Infections -- An Outline of an Expert System for Diagnosis and Treatment of Bronchogenic Carcinoma.
In: Springer Nature eBookSummary: This book constitutes the refereed proceedings of the 4th International Symposium on Medical Data Analysis, ISMDA 2003, held in Berlin, Germany in October 2003. The 15 revised full papers presented were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on medical models and learning, integration of intelligent analysis methods into medical databases, medical signal processing and image analysis, and applications of medical diagnostic support systems.
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Medical Models and Learning -- Possibility-Probability Relation in Medical Models -- How Exactly Do We Know Inheritance Parameters? -- Tuning of Diagnosis Support Rules through Visualizing Data Transformations -- Inductive Learning of Simple Diagnostic Scores -- Integration of Intelligent Analysis Methods into Medical Data Bases -- A Virtual Approach to Integrating Biomedical Databases and Terminologies -- Data Mining with Meva in MEDLINE -- Medical Signal and Image Analysis -- Isobologram Analysis in MATLAB for Combined Effects of Two Agents in Dose-Response Experiments -- Towards an Improved On-line Algorithm to Estimate the Fetal Heart Rate from Ultrasound Data -- Health Monitoring by an Image Interpretation System – A System for Airborne Fungi Identification -- Quantification and Characterization of Pulmonary Emphysema in Multislice-CT -- Interactive Visualization of Diagnostic Data from Cardiac Images Using 3D Glyphs -- Applications of Medical Diagnostic Support Systems -- Predicting Influenza Waves with Health Insurance Data -- Fuzzy Inference Systems for Multistage Diagnosis of Acute Renal Failure in Children -- Data Imbalance in Surveillance of Nosocomial Infections -- An Outline of an Expert System for Diagnosis and Treatment of Bronchogenic Carcinoma.

This book constitutes the refereed proceedings of the 4th International Symposium on Medical Data Analysis, ISMDA 2003, held in Berlin, Germany in October 2003. The 15 revised full papers presented were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on medical models and learning, integration of intelligent analysis methods into medical databases, medical signal processing and image analysis, and applications of medical diagnostic support systems.

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