Process Mining Techniques for Managing and Improving Healthcare Systems
CRC Press (Verlag)
978-1-032-43109-3 (ISBN)
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.
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.
1. Healthcare System. 2. Data Mining and Management Information Systems. 3. Process Mining and Big Data in Healthcare. 4. The Proposed β Algorithm for Healthcare Systems. 5. Building a Hospital Management Platform. 6. The Advantages of Using the MYL Platform.
| Erscheinungsdatum | 11.07.2023 |
|---|---|
| Zusatzinfo | 22 Tables, black and white; 58 Line drawings, black and white; 12 Halftones, black and white; 70 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 494 g |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Mathematik / Informatik ► Informatik ► Theorie / Studium | |
| Medizin / Pharmazie ► Gesundheitswesen | |
| Wirtschaft ► Volkswirtschaftslehre | |
| ISBN-10 | 1-032-43109-1 / 1032431091 |
| ISBN-13 | 978-1-032-43109-3 / 9781032431093 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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