Extracting Temporal Relationships in EHR: Application to COVID-19 Patients.

Association rules are one of the most used data mining techniques. The first proposals have considered relations over time in different ways, resulting in the so-called Temporal Association Rules (TAR). Although there are some proposals to extract association rules in OLAP systems, to the best of our knowledge, there is no method proposed to extract temporal association rules over multidimensional models in these kinds of systems. In this paper we study the adaptation of TAR to multidimensional structures, identifying the dimension that establishes the number of transactions and how to find time relative correlations between the other dimensions. A new method called COGtARE is presented as an extension of a previous approach proposed to reduce the complexity of the resulting set of association rules. The method is tested in application to COVID-19 patients data.

Evolution of tourism risk perception: A bibliometrics analysis on multi-dimensional model

How can we establish a risk perception model and method to guide safety management has become an important issue that needs to be solved urgently in the field of tourism management. However, the solution to this issue is inseparable from the objective analysis, induction and deduction, and the analysis of the frontier trend towards the multidimensional model of tourism risk perception. In this paper, 211 articles from the Web of Science are selected as the research object, and the bibliometric analysis is applied to find: (1) Research on tourism risk perception based on multidimensional models can be divided into nascent, developmental, and mature stages;(2) The research on the multi-dimensional model of tourism risk perception has formed a group of academic groups with outstanding contributions and representative authors;(3) The research hotspots in multidimensional models of tourism risk perception focus on the comprehensive study of perceived risk, the outbreak of COVID-19, psychological risk, destination image, and behavioral intention. On this basis, this paper proposes some corresponding research suggestions to address the inadequacies of existing studies, and the research findings have significant theoretical implications for the construction of the theoretical system of tourism risk management. © 2022 The Author(s).

Explore How Online Healthcare Can Influence Willingness to Seek Offline Care.

With the recent development of internet healthcare, many hospitals have laid out their online platforms. However, there have been some poor service levels and low quality. The frequency of such problems has led to a decline in patient satisfaction. Therefore, it is vital to explore how hospitals can improve user satisfaction and willingness to visit them offline by setting up an online presence. Most studies conducted so far have remained limited to the single dimension of online or offline healthcare, with few studies exploring the relationship between them. While a few studies have explored the impact of online service quality on willingness to seek offline care, they also face the problem of a single perspective of analysis. Therefore, this study constructs a multidimensional model of the factors influencing online healthcare users' willingness to seek offline care by integrating the value-based adoption model and the stimulus-organism-response model. Through a partial least squares-structural equation modelling analysis of 283 valid samples, this study found that online doctor-patient interactions and service quality positively impact user perception. This paper explores the development path of online healthcare from a new theoretical perspective. In addition, the findings provide new guidelines for hospitals to achieve economic and social benefits.

The Outcome of a New Teledentistry Initiative in Response to the COVID-19 Pandemic: A Cross-sectional Study.

AIM: The purpose of this study was to assess the overall satisfaction of a new learning experience and evaluate the outcome of LLUSD's educational teledentistry initiative through a survey based on Kirkpatrick's multidimensional model of training evaluation. MATERIALS AND METHODS: An IRB application was approved (#5210385) for a cross-sectional study that included Loma Linda University School of Dentistry (LLUSD) dental students of the class of 2022 and 2023. The 9-question survey consisted of three sections. The first section included demographic questions on gender and the graduating class. The second section was related to perceived teaching effectiveness, attitude, behavior, and significance. The third section included an open-ended question. The survey was distributed by three student investigators. Descriptive statistics were calculated, and categorical variables were compared using the Chi-squared test (χ2 test). RESULTS: The perceived teaching effectiveness of the newly implemented educational initiative was high for increasing the ability to communicate with patients and for screening and identifying the need for referrals. A majority of students believed that teledentistry is an important means to improve patients' access to dental care and that the School has been providing a good educational environment in providing teledentistry sessions to patients. There were no significant differences in the frequencies of positive and negative responses to all questions (N = 6) by gender and by class (p >0.05, in all instances). CONCLUSIONS: Teledentistry eVisits allowed the continuation of patient contact and initial assimilation of patient information. There is potential for this educational initiative to be more actively and comprehensively implemented in the future. CLINICAL SIGNIFICANCE: New educational initiatives allow the continuation of patient contact that will ensure that students will graduate as competent oral health care providers despite challenges imposed by the pandemic.

Data Analysis of Coronavirus CoVID-19: Study of Spread and Vaccination in European Countries

Humanity has gone since a long time through several pandemics, such as: H1N1 in 2009 and also Spanish flu in 1917. In December 2019, the health authorities of China detected unexplained cases of pneumonia. The WHO World Health Organization has declared the apparition of CoVID-19 (novel Coronavirus) that caused a global pandemic in 2020. In data analysis, multiple approaches and diverse techniques were used to extract useful information from multiple heterogeneous sources and to discover knowledge and new information for decision-making;it is used in different business and science domains. In this context, we propose to use the multidimensional analysis techniques based on two concepts: fact (subject of analysis) and dimensions (axes of analyses). This technique allows decision makers to observe data from various heterogeneous sources and analyze them according several viewpoints or perspectives. More precisely, we propose a multidimensional model for analyzing the Coronavirus CoVID-19 data (spread and vaccination in European countries). This model is based on constellation schema that contains several facts surrounded by common dimensions © 2022, International Journal of Advanced Computer Science and Applications. All Rights Reserved.