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DC Field | Value | Language |
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dc.contributor.author | Renugadevi R, R | - |
dc.contributor.author | Ranjith Kumar, P | - |
dc.contributor.author | Kalaiarasi, G | - |
dc.contributor.author | Raj A, Arul Edwin | - |
dc.contributor.author | Settu, Sivabalan | - |
dc.contributor.author | Ruthravarshini, R | - |
dc.date.accessioned | 2024-09-11T07:07:18Z | - |
dc.date.available | 2024-09-11T07:07:18Z | - |
dc.date.issued | 2024-07-23 | - |
dc.identifier.isbn | 979-836937459-7 | - |
dc.identifier.uri | https://www.igi-global.com/gateway/chapter/351587 | - |
dc.description.abstract | This chapter outlines the need for intelligent decision support, growing complexity of healthcare systems, key concepts of advanced analytics, and elucidating techniques such as data preprocessing and feature engineering. The survey extends to address challenges and opportunities within the realm of healthcare analytics, offering insights into ethical considerations, privacy concerns, and regulatory implications. Real-world case studies serve to illuminate successful implementations and extract valuable lessons, fostering a deeper understanding of practical applications. This chapter explores the integration of analytics with electronic health records (EHR), examining strategies to enhance decision support through the utilization of comprehensive healthcare data. The chapter, by distilling pertinent information from myriad sources, aims to provide a valuable resource for researchers, practitioners, and policymakers navigating the dynamic intersection of advanced analytics, machine learning, and healthcare decision support systems. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | IGI Global | en_US |
dc.title | ENHANCING HEALTHCARE DECISION SUPPORT SYSTEMS WITH ADVANCED ANALYTICS AND MACHINE LEARNING TECHNIQUES | en_US |
dc.type | Book chapter | en_US |
Appears in Collections: | 3.Book Chapter (18) |
Files in This Item:
File | Description | Size | Format | |
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ENHANCING HEALTHCARE DECISION SUPPORT SYSTEMS WITH ADVANCED ANALYTICS AND MACHINE LEARNING TECHNIQUES.docx | 593.9 kB | Microsoft Word XML | View/Open |
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