Application of Advanced Optimization Techniques for Healthcare AnalyticsКНИГИ » ПРОГРАММИНГ
Название: Application of Advanced Optimization Techniques for Healthcare Analytics Автор: Mohamed Abdel-Basset, Ripon K. Chakrabortty, Reda Mohamed Издательство: CRC Press Год: 2023 Страниц: 245 Язык: английский Формат: pdf (true) Размер: 33.5 MB
Many different optimization techniques and methods have been applied in healthcare, ranging from the decision of the operational levels to the design of national healthcare policies. Healthcare facility location, capacity planning, disease screening, and medical human resource scheduling are a few examples, while different optimization techniques and decision analytics (i.e., predictive analytics, prescriptive models) are being successfully used. Besides the traditional optimization concepts, different advanced Deep Learning (DL) and Machine Learning (ML) models have also grasped good perspectives in healthcare analytics. For instance, the application of advanced ML or DL models for medical imaging, biomedical signal processing, and DNA microarray data analysis are a few examples.
While the contributions of existing works of literature and their influence on hospital analytics are undeniable, the necessity of better ML or DL approaches, advanced augmentation of ML/DL approaches with metaheuristics, better design of classical optimization tools (e.g., bi- level optimization, nested optimization) are also irrefutable. In addition to the need for advanced solution approaches, the design and articulation of healthcare problems (e.g., home healthcare scheduling, biological sample transportation network, facility location problem, nutrition decision support system, nurse scheduling, smart healthcare scheduling problems) are also evident, particularly during such a tiring era (post-pandemic). Therefore, a combination of better problem architecture and advanced solution approaches to overarching hospital analytics is a must and should be considered for practitioners, undergraduate and postgraduate students, and, most importantly, for higher degree research students.
Application of Advanced Optimization Techniques for Healthcare Analytics, 1st Edition, is an excellent compilation of current and advanced optimization techniques which can readily be applied to solve different hospital management problems. The healthcare system is currently a topic of significant investigation to make life easier for those who are disabled, old, or sick, as well as for young children. The emphasis of the healthcare system has evolved throughout time due to several emerging beneficial technologies, such as personal digital assistants (PDAs), data mining, the internet of things, metaheuristics, fog computing, and cloud computing.
Metaheuristics are strong technology for tackling several optimization problems in various fields, especially healthcare systems. The primary advantage of metaheuristic algorithms is their ability to find a better solution to a healthcare problem and their ability to consume as little time as possible. In addition, metaheuristics are more flexible compared to several other optimization techniques. These algorithms are not related to a specific optimization problem but could be applied to any optimization problem by making some small adaptations to become suitable to tackle it.
The successful outcome of this book will enable a decision-maker or practitioner to pick a suitable optimization approach when making decisions to schedule patients under crowding environments with minimized human errors.
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Application of Advanced Optimization Techniques for Healthcare Analytics 
Название: Application of Advanced Optimization Techniques for Healthcare Analytics
