Evaluation of Smart Healthcare Systems and Novel UV-Oriented Solution for Integration, Resilience, Inclusiveness and Sustainability

Zhang, Lifeng; Ren, Justin; Yuan, Hao; Yang, Zhaohui; Wang, Weishi; Guo, Mingxiao; Cheng, Guanghua; Zhou, Lei; Tao, Stanley; Zhang, Lin; Cui, Hongyan; Fang, Yajun

doi:10.1109/uv50937.2020.9426210

Cited by 6 publications

(7 citation statements)

References 99 publications

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“…Besides, the future of data mining is intact, and there is a slight hope of having increased efficiency. [21] Previous studies Previous studies Clustering Clustering [19] Previous studies Previous studies Data analysis PAM, CLARA, DBSCAN, and multiple linear regression [29] Previous studies Previous studies Clustering DBSCAN [24] Previous studies Previous studies Clustering Clustering [30] Previous studies Previous studies Data analysis CLARA [28] Previous studies Previous studies Data analysis Association…”

Section: Discussionmentioning

confidence: 99%

“…It was later discovered that the values and prospects of the data mining technique were based on the availability of this drive from the management [27]. Hence, if the management has fully embraced the data mining technique, it becomes easy for the firms to grow and realize a huge potential in the market [23,28].…”

Section: Potential Of Data Mining To Support Business Modelmentioning

confidence: 99%

“…Organisation datasets can leverage the association to identify certain groups of claims that are likely to be submitted electronically, on paper, or through a web portal. e system may use this data to create numerous BI dashboards and analyses about the intake process [28]. In claim processing, data processing is also utilised to recover and uncover additional patterns.…”

Section: Impact Of Data Mining Techniques On Business Modelmentioning

confidence: 99%

“…Multiple additive trees (MATs), or gradient boosting, is a novel improvement in data mining introduced by Friedman at Stanford University. It uses stochastic gradient boosting to extend and improve the decision tree (DT) model [28]. Boosting is a broad strategy for attempting to "boost" the efficiency of any given classification model by fitting a series of limited models and then combining them.…”

Section: Impact Of Data Mining Techniques On Business Modelmentioning

confidence: 99%

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Data Mining and Soft Computing in Business Model for Decision Support System

Gazzawe

Alturki

2022

Scientific Programming

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Several studies were taken to effectively determine the importance of data mining in business model development for decision support system. It was later discovered that most businesses have invested heavily in the data mining process which enables them to easily study and analyse the market environment and improve their domination in the market. Data mining is a process used by most firms to effectively collect information about certain topic. One factor that business model development usually focuses more on is the value of measurable performance and increased innovation in the market. The aim of the current research is to investigate the values and key roles played by data mining prospects in the business model development. It also revolves around current techniques used within business model development that are crucial in enhancing the position and competitiveness of a firm in the market. Although the data mining prowess varies in regards to the firm and effort used, the main concept remains on how to fully have the firm understand the effects and role played by data mining techniques in their overall business flow. In methodology, secondary sources are categorically used to enhance the overall flow of the study question by comparing them and analyzing them using the techniques provided. The results and analysis reveal that the effects of using data mining techniques are huge towards achieving success for various businesses. Moreover, the practical implications have categorically increased the notion of how influential the prospects of data mining can be when applied in businesses.

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Section: Discussionmentioning

confidence: 99%

Section: Potential Of Data Mining To Support Business Modelmentioning

confidence: 99%

Section: Impact Of Data Mining Techniques On Business Modelmentioning

confidence: 99%

Section: Impact Of Data Mining Techniques On Business Modelmentioning

confidence: 99%

See 2 more Smart Citations

Data Mining and Soft Computing in Business Model for Decision Support System

Gazzawe

Alturki

2022

Scientific Programming

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“…IT-intensive, financial, etc.) 35 – 38 or have not proposed any method for assessment, 39 , 40 the methods mentioned in seven references were compared. In addition, in this table, only the properties of these methods are compared based on explicit facts, without subjective judgments.…”

Section: Introductionmentioning

confidence: 99%

Assessing the sustainability of smart healthcare applications using a multi-perspective fuzzy comprehensive evaluation approach

Wu,

Chen,

Chiu

2023

DIGITAL HEALTH

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A smart healthcare application can be judged as sustainable if it was already widely used before and will also be prevalent in the future. In contrast, if a smart healthcare application developed during the COVID-19 pandemic is not used after it, then it is not sustainable. Assessing the sustainability of smart healthcare applications is a critical task for their users and suppliers. However, it is also a challenging task due to the availability of data, users’ subjective beliefs, and different perspectives. In response to this problem, this study proposes a multi-perspective fuzzy comprehensive evaluation approach to evaluate the sustainability of a smart healthcare application from qualitative, multi-criteria decision-making and time-series perspectives. The proposed methodology has been used to evaluate the sustainability of eight smart healthcare applications. The experimental results showed that the sustainability of a smart healthcare application evaluated from different perspectives may be different. Nevertheless, another technique can be used to confirm the evaluation result generated using one technique. In other words, these views compensate for each other.

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Preliminary Exploration and Evaluation of Smart Support for Homeless Community

Wang¹,

Fang²

2022

2022 6th International Conference on Universal Village (UV)

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Evaluation of Smart Healthcare Systems and Novel UV-Oriented Solution for Integration, Resilience, Inclusiveness and Sustainability

Cited by 6 publications

References 99 publications

Data Mining and Soft Computing in Business Model for Decision Support System

Data Mining and Soft Computing in Business Model for Decision Support System

Assessing the sustainability of smart healthcare applications using a multi-perspective fuzzy comprehensive evaluation approach

Preliminary Exploration and Evaluation of Smart Support for Homeless Community

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