Remote Care Assistance in Emergency Department Based on Smart Medical

Zhou, Chengli; Hu, Juan

doi:10.1155/2021/9971960

Cited by 10 publications

(6 citation statements)

References 28 publications

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“…Remote care: AI can help monitor patients remotely, which can be particularly useful for people living in remote areas or those with mobility issues to enable access to healthcare services ( 53 , 69 , 70 ).…”

Section: Advantages and Disadvantages Of Artificial Intelligence In M...mentioning

confidence: 99%

Artificial Intelligence in Medicine and Dentistry

Vodanović¹,

Subašić²,

Milošević³

et al. 2023

Acta Stomatol Croat

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Introduction Artificial intelligence has been applied in various fields throughout history, but its integration into daily life is more recent. The first applications of AI were primarily in academia and government research institutions, but as technology has advanced, AI has also been applied in industry, commerce, medicine and dentistry. Objective Considering that the possibilities of applying artificial intelligence are developing rapidly and that this field is one of the areas with the greatest increase in the number of newly published articles, the aim of this paper was to provide an overview of the literature and to give an insight into the possibilities of applying artificial intelligence in medicine and dentistry. In addition, the aim was to discuss its advantages and disadvantages. Conclusion The possibilities of applying artificial intelligence to medicine and dentistry are just being discovered. Artificial intelligence will greatly contribute to developments in medicine and dentistry, as it is a tool that enables development and progress, especially in terms of personalized healthcare that will lead to much better treatment outcomes.

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Section: Advantages and Disadvantages Of Artificial Intelligence In M...mentioning

confidence: 99%

Artificial Intelligence in Medicine and Dentistry

Vodanović¹,

Subašić²,

Milošević³

et al. 2023

Acta Stomatol Croat

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“…Mobile Information Systems information asymmetry, unreasonable allocation of medical resources, and other problems [21].…”

Section: Related Workmentioning

confidence: 99%

Research on Urban Intelligent Medical Service System Design Based on Multiobjective Decision-Making Optimization Strategy

Huang

2022

Mobile Information Systems

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Aiming at the problems of difficult medical treatment for urban residents, low efficiency of hospitals, imbalance of medical resources and difficulty to meet the demands of patients, this paper proposes an urban intelligent medical service system based on multiobjective decision-making optimization strategy. Firstly, it analyzes the medical service demands of urban residents and points out that the urban intelligent medical service system should provide comprehensive services for residents; the main demands include basic medical demands, expected medical demands, and health care medical demands. Secondly, based on demand analysis, an urban intelligent medical service system composed of government, community hospital, large hospital, and urban residents is designed. The system has three kinds of system functions: customer business services, basic services, and institutional information services. Then, the overall process of the system before and after treatment of urban residents is introduced. Finally, according to the optimization objectives of the system: low medical cost, fast treatment speed, and high service satisfaction, the corresponding optimization strategies are formulated to optimize the urban intelligent medical system, reduce medical cost, improve treatment speed, and improve customer satisfaction, to better serve urban residents.

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“…Such a terminal can also collect and transmit data to the database of a back-end system through a network or other wireless communication system. Therefore, potential applications of IoT have been discussed in many different domains [10], including transportation logistics [11][12][13], industrial manufacturing [14][15][16][17][18][19], and health care [20][21][22][23][24][25]. In aquaculture, IoT is also used for water quality inspection [26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence in Internet of Things System for Predicting Water Quality in Aquaculture Fishponds

Yang¹,

Liao²,

Chou³

2023

Computer Systems Science and Engineering

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Aquaculture has long been a critical economic sector in Taiwan. Since a key factor in aquaculture production efficiency is water quality, an effective means of monitoring the dissolved oxygen content (DOC) of aquaculture water is essential. This study developed an internet of things system for monitoring DOC by collecting essential data related to water quality. Artificial intelligence technology was used to construct a water quality prediction model for use in a complete system for managing water quality. Since aquaculture water quality depends on a continuous interaction among multiple factors, and the current state is correlated with the previous state, a model with time series is required. Therefore, this study used recurrent neural networks (RNNs) with sequential characteristics. Commonly used RNNs such as long short-term memory model and gated recurrent unit (GRU) model have a memory function that appropriately retains previous results for use in processing current results. To construct a suitable RNN model, this study used Taguchi method to optimize hyperparameters (including hidden layer neuron count, iteration count, batch size, learning rate, and dropout ratio). Additionally, optimization performance was also compared between 5-layer and 7-layer network architectures. The experimental results revealed that the 7-layer GRU was more suitable for the application considered in this study. The values obtained in tests of prediction performance were mean absolute percentage error of 3.7134%, root mean square error of 0.0638, and R-value of 0.9984. Therefore, the water quality management system developed in this study can quickly provide practitioners with highly accurate data, which is essential for a timely response to water quality issues. This study was performed in collaboration with the Taiwan Industrial Technology Research Institute and a local fishery company. Practical application of the system by the fishery company confirmed that the monitoring system is effective in improving the survival rate of farmed fish by providing data needed to maintain DOC higher than the standard value.

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Remote Care Assistance in Emergency Department Based on Smart Medical

Cited by 10 publications

References 28 publications

Artificial Intelligence in Medicine and Dentistry

Artificial Intelligence in Medicine and Dentistry

Research on Urban Intelligent Medical Service System Design Based on Multiobjective Decision-Making Optimization Strategy

Artificial Intelligence in Internet of Things System for Predicting Water Quality in Aquaculture Fishponds

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