Intervention of population health management innovation on economy based on cognitive computing |
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| Institution: | 1. AGH University of Science and Technology, 30 Mickiewicza Ave, Kraków 30-059, Poland;2. VSB Technical University of Ostrava, 17. listopadu 2172/15, Ostrava-Poruba 708 00, Czech Republic;1. School of Information and Communication Engineering, Hunan Institute of Science and Technology, Hunan, China;2. Machine Vision & Artificial Intelligence Research Center, Hunan Institute of Science and Technology, Hunan, China;1. School of Economics and Management, Chang''an University, Xi''an 710064, China;2. Computer & Information Sciences Department, Universiti Teknologi PETRONAS, 32610 Seri Iskandar, Perak, Malaysia;3. Institute of IR4.0, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia;4. College of Engineering, Al Ain University, Al Ain, United Arab Emirates;5. Department of Mathematics, College of Science, Tafila Technical University, Tafila, Jordan;1. Ryerson University;2. Arizona State University;3. Illinois Institute of Technology;4. University of Guelph |
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| Abstract: | With the emergence of Delta strains in many regions of China, population health issues have aroused great concern in many industries. Therefore, it is necessary to intervene in population health management through a variety of means. This paper establishes an economic intervention model of cognitive computing to evaluate the health of population health management innovation, track the health risks of the population and actively manage the relationship between population health. This paper establishes a health assessment model based on cognitive computing and uses a population health survey to evaluate the physical condition, illness, and life index of 64 citizens in this city before and after the economic intervention. The results of the study show that when economic dynamics test indicators are added to the prediction model of the post-test scores of economic intervention and health status, the explanatory power R2 of the cognitive computing model increased by 4.8% and 3.5%, respectively. The score (β=0.36, p <0.001), IPDT ( Inventory of Piaget's Developmental Tas) intervention score (β=0.15, p = 0.025) and migration score (β=0.18, p = 0.012) can significantly predict the post-economic intervention test score (R2=51.2%, p <0.001). The pre-test score on the health status test (β=0.48, p <0.001) and the IPDT intervention score (β=0.25, p = 0.014) can significantly predict the health status post-test score (R2=32.54%, p <0.001). |
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