Data Mining in Medicine

Beatrice Amico; Carlo Combi; Yuval Shahar

doi:https://doi.org/10.1007/978-3-031-24628-9_27

Data Mining in Medicine

Beatrice Amico, Carlo Combi, Yuval Shahar

Department of Software and Information Systems Engineering

Ben-Gurion University of the Negev

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

Clinical databases collect large volumes of information. Relationships and patterns within these data could provide new medical knowledge. Data mining has as major objective the discovery of knowledge from large amounts of data, offers many possibilities for identifying different data features less visible or hidden to common analysis techniques. This chapter focuses on a selection of techniques and illustrates their applicability to medical diagnostic and prognostic problems.

Original language	American English
Title of host publication	Machine Learning for Data Science Handbook
Subtitle of host publication	Data Mining and Knowledge Discovery Handbook, Third Edition
Pages	607-636
Number of pages	30
ISBN (Electronic)	9783031246289
DOIs	https://doi.org/10.1007/978-3-031-24628-9_27
State	Published - 1 Jan 2023

All Science Journal Classification (ASJC) codes

General Computer Science
General Mathematics

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AU - Combi, Carlo

AU - Shahar, Yuval

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AB - Clinical databases collect large volumes of information. Relationships and patterns within these data could provide new medical knowledge. Data mining has as major objective the discovery of knowledge from large amounts of data, offers many possibilities for identifying different data features less visible or hidden to common analysis techniques. This chapter focuses on a selection of techniques and illustrates their applicability to medical diagnostic and prognostic problems.

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BT - Machine Learning for Data Science Handbook

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Data Mining in Medicine

Abstract

All Science Journal Classification (ASJC) codes

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