Process Mining Techniques for Managing and Improving Healthcare Systems

Maha Zayoud

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Hardback

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English

CRC Press
26 June 2023

Health systems & services; Data capture & analysis; Data mining

This book discusses a new process mining method along with a detailed comparison between different techniques that provide a complete vision of the process of data acquisition, data analysis, and data prediction.

Process Mining Techniques for Managing and Improving Healthcare Systems offers a new framework for process learning which is probabilistic and enables the process to be learned in an accumulative manner. The steps of prediction modeling and building the required knowledge are highlighted throughout the book, along with a strong emphasis on the correlation between the healthcare domain and technology including the different aspects, such as: managing records, information, and procedures; early detection of diseases; and the improvement of accuracy in choosing the right treatment procedures.

This reference provides a wealth of knowledge for practitioners, researchers, and students at the basic and intermediary levels working within the healthcare system, computer science, electronics and communications, as well as medical providers and also hospital management entities.

By: Maha Zayoud
Imprint: CRC Press
Country of Publication: United Kingdom
Dimensions: Height: 234mm, Width: 156mm,
Weight: 494g
ISBN: 9781032431093
ISBN 10: 1032431091
Pages: 24
Publication Date: 26 June 2023
Audience: College/higher education , Professional and scholarly , Primary , Undergraduate
Format: Hardback
Publisher's Status: Active

Maha Zayoud was born in Damascus, Syria, in 1985. She holds PHD degree in the field of industrial engineering from Politehnica University of Bucharest, Romania. B.S. and M.S. degrees in computer engineering from Kuwait University, Kuwait. She is currently with the Department of Computer Engineering, at the College of Engineering and Technology, the American University of the Middle East, Kuwait. Her research interests include machine learning, data and process mining, big data, industrial management systems, and intelligent engineering designs.