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Titlebook: Healthcare 4.0; Next Generation Proc Janya Chanchaichujit,Albert Tan,Sarayoot Eaimkhong Book 2019 The Editor(s) (if applicable) and The Aut

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樓主: exposulate
31#
發(fā)表于 2025-3-26 23:01:38 | 只看該作者
32#
發(fā)表于 2025-3-27 04:00:10 | 只看該作者
Janya Chanchaichujit,Albert Tan,Fanwen Meng,Sarayoot EaimkhongAllergic rhinitis is a common condition with a diverse differential diagnosis and multiple therapeutic options. Optimizing treatment by verifying the diagnosis and directing therapy to the most bothersome symptoms will result in improved quality of life.
33#
發(fā)表于 2025-3-27 09:10:53 | 只看該作者
Innovative Health Technologies and Start-Ups Process in Healthcare Industry,This chapter discusses an innovative health technology and development process in the healthcare industry, challenges and trends in the healthcare system, and health technologies for the future. The chapter concludes by recommending methodologies for developing health technology to start-ups and entrepreneurs.
34#
發(fā)表于 2025-3-27 13:19:26 | 只看該作者
35#
發(fā)表于 2025-3-27 14:02:49 | 只看該作者
Janya Chanchaichujit,Albert Tan,Sarayoot EaimkhongProvides an overview of the Internet of Things, Big Data Analytics, Blockchain, Optimization and Predictive Analytics at work in healthcare.Outlines a strategic framework to exploit new technologies t
36#
發(fā)表于 2025-3-27 19:55:29 | 只看該作者
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37#
發(fā)表于 2025-3-27 23:48:27 | 只看該作者
https://doi.org/10.1007/978-981-13-8114-0Healthcare 4; 0 in Singapore; Internet of Things Application in Singapore Healthcare; Big Data Analytic
38#
發(fā)表于 2025-3-28 05:48:51 | 只看該作者
Janya Chanchaichujit,Albert Tan,Fanwen Meng,Sarayoot Eaimkhongof the most common examples of these immunological diseases. On a daily basis, physicians obtain an allergy history before prescribing any antibiotic because of the high incidence of drug reactions in the population, illustrating one example of the importance of these disorders in clinical medicine.
39#
發(fā)表于 2025-3-28 07:32:54 | 只看該作者
Application of Artificial Intelligence in Healthcare,The complexity of the disease and problems in TB diagnosis are introduced. Following this, initiatives and opportunities for using AI in TB diagnosis in Thailand are shown as a case study. The chapter concludes by discussing the current limitations of AI improvement, alternative models and key success factors in the implementation of AI in TB.
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