Data Mining Approaches forHealthcare Decision Support Systems

Title

Data Mining Approaches forHealthcare Decision Support Systems

Creator

Pramanik S.; Galety M.G.; Samanta D.; Joseph N.P.

Description

Data mining is a user-friendly approach to locating previously unknown or hidden information in data. The employment of data mining technologies in the healthcare system may result in the finding of relevant data. Data mining is used in healthcare medicine to construct learning models that predict a patients condition. Data mining technologies have the potential to benefit all stakeholders in the healthcare industry. For example, data mining may aid health providers in detecting theft and fraud, medical organizations in making customer service management decisions, physicians in discovering effective therapies and best practices, and customers in obtaining suitable and less expensive healthcare. Contemporary systems, due to their complexity and size, are unable to control and analyze the huge amounts of data generated by healthcare operations. Data mining is a technique and mechanism for converting a large amount of data into useful information. The fundamental purpose of this research is to look at what makes clinical data mining unique, to give an overview of existing clinical decision support systems, to identify and select the most common data mining algorithms used in modern Health and Demographic Surveillance System (HDSS), and to compare different data mining algorithms. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Source

Lecture Notes in Networks and Systems, Vol-490, pp. 721-733.

Date

2023-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Bayes; C4.5; Clinical decision support system; HDSS; WEKA

Coverage

Pramanik S., Department of CSE, Haldia Institute of Technology, West Bengal, Haldia, India; Galety M.G., College of Information Technology and Computer Science, Catholic University in Erbil, Erbil, Iraq; Samanta D., Department of Computer Science, CHRIST University, Karnataka, Bangalore, India; Joseph N.P., Department of Computer Science, CHRIST University, Karnataka, Bangalore, India

Rights

Restricted Access

Relation

ISSN: 23673370; ISBN: 978-981194051-4

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-19-4052-1_71

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