A simple powerful bivariate test for two sample location problems in experimental and observational studies

<p>Abstract</p> <p>Background</p> <p>In many areas of medical research, a bivariate analysis is desirable because it simultaneously tests two response variables that are of equal interest and importance in two populations. Several parametric and nonparametric bivariate procedures are available for the location problem but each of them requires a series of stringent assumptions such as specific distribution, affine-invariance or elliptical symmetry.</p> <p>The aim of this study is to propose a powerful test statistic that requires none of the aforementioned assumptions. We have reduced the bivariate problem to the univariate problem of sum or subtraction of measurements. A simple bivariate test for the difference in location between two populations is proposed.</p> <p>Method</p> <p>In this study the proposed test is compared with Hotelling's <it>T</it>²test, two sample Rank test, Cramer test for multivariate two sample problem and Mathur's test using Monte Carlo simulation techniques. The power study shows that the proposed test performs better than any of its competitors for most of the populations considered and is equivalent to the Rank test in specific distributions.</p> <p>Conclusions</p> <p>Using simulation studies, we show that the proposed test will perform much better under different conditions of underlying population distribution such as normality or non-normality, skewed or symmetric, medium tailed or heavy tailed. The test is therefore recommended for practical applications because it is more powerful than any of the alternatives compared in this paper for almost all the shifts in location and in any direction.</p

Studying Students' Knowledge of the Benefits, Challenges, and Applications of Big Data Analytics in Healthcare

The purpose of this study was to evaluate the students' familiarity from different universities of Mashhad with the benefits, applications and challenges of Big Data analysis. This is a cross-sectional study that was conducted on students of different fields, including Medical Engineering, Medical Informatics, Medical Records and Health Information Management in Mashhad-Iran. A questionnaire was designed. The designed questionnaire evaluated the opinion of students regarding benefits, challenges and applications of Big Data analytics. 200 students participated and participants' opinions were evaluated descriptively and analytically. Most students were between 20 and 30 years old. 43.5% had no work experience. Current and previous field of study of most of the students were HIT, HIM, and Medical Records. Most of the participants in this study were undergraduates. 61.5% were economically active, 54.5% were exposed to Big Data. The mean scores of participants in benefits, applications, and challenges section were 3.71, 3.68, and 3.71, respectively, and process management was significant in different age groups (p=0.046), information, modelling, research, and health informatics across different fields of studies were significant (p=0.015, 0.033, 0.001, 0.024) Information and research were significantly different between groups (p=0.043 and 0.019), research in groups with / without economic activity was significant (p= 0.017) and information in exposed / non-exposed to Big Data groups was significant (p=0.02). Despite the importance and benefits of Big Data analytics, students' lack of familiarity with the necessity and importance is significant. The field of study and level of study does not appear to have an effect on the degree of knowledge of individuals regarding Big Data analysis. The design of technical training courses in this field may increase the level of knowledge of individuals regarding Big Data analysis

Investigating Evaluation Frameworks for Electronic Health Record: A Literature Review

BACKGROUND: There are various electronic health records (EHRs) evaluation frameworks with multiple dimensions and numerous sets of evaluation measures, while the coverage rate of evaluation measures in a common framework varies in different studies. AIM: This study provides a literature review of the current EHR evaluation frameworks and a model for measuring the coverage rate of evaluation measures in EHR frameworks. METHODS: The current study was a comprehensive literature review and a critical appraisal study. The study was conducted in three phases. In Phase 1, a literature review of EHR evaluation frameworks was conducted. In Phase 2, a three-level hierarchical structure was developed, which includes three aspects, 12 dimensions, and 110 evaluation measures. Subsequently, evaluation measures in the identified studies were categorized based on the hierarchical structure. In Phase 3, relative frequency (RF) of evaluation measures in different dimensions and aspects for each of the identified studies were determined and categorized as follows: Appropriate, moderate, and low coverage. RESULTS: Out of a total of 8276 retrieved articles, 62 studies were considered relevant. The RF range in the second and third level of the hierarchical structure was between 8.6%–91.94% and 0.2%–61%, respectively. “Ease of use” and “system quality” were the most frequent evaluation measure and dimension. Our results indicate that identified studies cover at least one and at most nine evaluation dimensions and current evaluation frameworks focus more on the technology aspect. Almost in all identified studies, evaluation measures related to the technology aspect were covered. However, evaluation measures related to human and organization aspects were covered in 68% and 84% of the identified studies, respectively. CONCLUSION: In this study, we systematically reviewed all literature presenting any type of EHR evaluation framework and analyzed and discussed their aspects and features. We believe that the findings of this study can help researchers to review and adopt the EHR evaluation frameworks for their own particular field of usage

A Survey of Students’ Attitudes to Big Data Analysis in Iranian Universities

Today, with the emergence of new technologies and massive data, big data analysis has attracted the attention of researchers, industries and universities on a global scale. The present research aims to explore students’ attitude to big data analysis in different fields of study. The present cross-sectional study was conducted with students at different universities and fields of study in Iran. A questionnaire was developed. This questionnaire explored students’ attitude toward big data analysis. To this aim, 359 university students participated in the research. The data were analyzed using descriptive and inferential statistics. The age of the students ranged between 25 and 34 years. 55.2% were female and 54% were economically active. 40.9% had a work experience of less than a year. The academic degree of the majority of participants was master’s degree. 93.9% of the participants believed that big data analysis was essential for the country. 43.2% maintained that big data mostly belonged to the communication industry. 28.1% perceived MATLAB useful software for analysis. 40.9% were familiar with the benefits of analysis. Engage in economic activities, less than 1 year of experience and studies for a Master’s degree showed to be significantly correlated with familiarity with the benefits of big data (p≤0.01). Such issues as high costs, managers’ unfamiliarity and lack of expertise and complexity were raised by the respondents. Considering the undeniable benefits of big data analysis, it seems essential to familiarize university students with these analyses through particular training courses, conferences and so on

Accuracy of CBCT, Digital Radiography and Cross-Sectioning for the Evaluation of Mandibular Incisor Root Canals

ntroduction: The aim of this study was to compare the accuracy of cone-beam computed tomography (CBCT), digital radiography and tooth sectioning in evaluating root canal morphology of mandibular incisors in an in vitro setting. Methods and Materials: A total of 76 samples were imaged using CBCT, and digital radiography in straight and angled views. The samples were then sectioned at different distances from the apex for further visualization under stereomicroscope. The agreement between the observers was statistically analyzed by kappa correlation coefficient and the chi-square test. Results: The results showed that the majority of the samples had a single canal (Vertucci’s Type I). CBCT analysis reported more frequent multi-canal roots in comparison with the other techniques. In pairwise comparisons, the highest agreement was found between digital radiographic imaging and microscopic cross-sectioning both in terms of canal configuration and the number of root canals. Conclusion: None of the used imaging techniques per se could adequately show the exact internal anatomical configuration in accordance with the gold standard.Keywords: Anatomy; Cone-Beam Computed Tomography; Digital Radiography; Incisor Teet

Comparing morphologic features and complications of main clear corneal incision between junior and senior residents observed using anterior segment optical coherence tomography

Background: Wound construction is a critical step in phacoemulsification. Using anterior segment optical coherence tomography (AS-OCT), we compared the morphological features and complications of main incisions made by junior or senior residents during phacoemulsification. Methods: This cross-sectional comparative study included eyes with senile cataracts that underwent uneventful phacoemulsification with a clear corneal incision made by seven senior and eight junior ophthalmology residents. All eyes underwent postoperative image acquisition using AS-OCT on day one and at three months, examining for morphological features and potential complications of the main incision. Results: We included 50 eyes of 50 patients with a male-to-female ratio of 22 (44%) to 28 (56%); 26 (52%) were operated on by junior residents and 24 (48%) by seniors. The mean geometric features of the main incisions and the frequency of early and late wound complications were comparable between the two groups (all&nbsp;P&nbsp;&gt; 0.05). A significant correlation was found between the incision length and angle with the superior (r = + 0.80;&nbsp;P&nbsp;&lt; 0.001 and r = - 0.63;&nbsp;P&nbsp;&lt; 0.001, respectively) and inferior (r = + 0.84;&nbsp;P&nbsp;&lt; 0.001 and r = - 0.68;&nbsp;P&nbsp;&lt; 0.001, respectively) areas of the incision, as well as between the length and angle of incision (r = - 0.74;&nbsp;P&nbsp;&lt; 0.001). The number of planes in the wound architecture was not significantly different according to senior or junior resident status (P&nbsp;&gt; 0.05). Although the number of eyes with stromal hydration was significantly greater for junior residents than for seniors (P&nbsp;&lt; 0.001), the corneal thickness at the entrance to the cornea or the anterior chamber, presence of endothelial wound gaping, and Descemet’s membrane detachment were comparable between eyes with and without stromal hydration (all&nbsp;P&nbsp;&gt; 0.05). At three months, 29 (58%) patients returned for examination, in whom seven (24%) had late wound complications. Conclusions: This study found no significant differences in the performances of junior and senior residents in terms of wound construction or its associated complications. However, considering the overall rate of some observed wound-related complications, we recommended revision of the resident educational curriculum concerning the structure and complications of the main incision

Expert opinions on informational and supportive needs and sources of obtaining information in patients with inflammatory bowel disease: a Delphi consensus study

BackgroundThe present study introduces informational and supportive needs and sources of obtaining information in patients with inflammatory bowel disease (IBD) through a three-round Expert Delphi Consensus Opinions method.MethodsAccording to our previous scoping review, important items in the area of informational and supportive needs and sources of obtaining information were elucidated. After omitting duplicates, 56 items in informational needs, 36 items in supportive needs, and 36 items in sources of obtaining information were retrieved. Both open- and close-ended questions were designed for each category in the form of three questionnaires. The questionnaires were sent to selected experts from different specialties. Experts responded to the questions in the first round. Based on the feedback, questions were modified and sent back to the experts in the second round. This procedure was repeated up to the third round.ResultsIn the first round, five items from informational needs, one item from supportive needs, and seven items from sources of obtaining information were identified as unimportant and omitted. Moreover, two extra items were proposed by the experts, which were added to the informational needs category. In the second round, seven, three, and seven items from informational needs, supportive needs, and sources of obtaining information were omitted due to the items being unimportant. In the third round, all the included items gained scores equal to or greater than the average and were identified as important. Kendall coordination coefficient W was calculated to be 0.344 for information needs, 0.330 for supportive needs, and 0.325 for sources of obtaining information, indicating a fair level of agreement between experts.ConclusionsOut of 128 items in the first round, the omission of 30 items and the addition of two items generated a 100-item questionnaire for three sections of informational needs, supportive needs, and sources of obtaining information with a high level of convergence between experts' viewpoints

Decision fusion in healthcare and medicine : a narrative review

Objective: To provide an overview of the decision fusion (DF) technique and describe the applications of the technique in healthcare and medicine at prevention, diagnosis, treatment and administrative levels. Background: The rapid development of technology over the past 20 years has led to an explosion in data growth in various industries, like healthcare. Big data analysis within the healthcare systems is essential for arriving to a value-based decision over a period of time. Diversity and uncertainty in big data analytics have made it impossible to analyze data by using conventional data mining techniques and thus alternative solutions are required. DF is a form of data fusion techniques that could increase the accuracy of diagnosis and facilitate interpretation, summarization and sharing of information. Methods: We conducted a review of articles published between January 1980 and December 2020 from various databases such as Google Scholar, IEEE, PubMed, Science Direct, Scopus and web of science using the keywords decision fusion (DF), information fusion, healthcare, medicine and big data. A total of 141 articles were included in this narrative review. Conclusions: Given the importance of big data analysis in reducing costs and improving the quality of healthcare; along with the potential role of DF in big data analysis, it is recommended to know the full potential of this technique including the advantages, challenges and applications of the technique before its use. Future studies should focus on describing the methodology and types of data used for its applications within the healthcare sector

Modifying the false discovery rate procedure based on the information theory under arbitrary correlation structure and its performance in high-dimensional genomic data

Abstract Background Controlling the False Discovery Rate (FDR) in Multiple Comparison Procedures (MCPs) has widespread applications in many scientific fields. Previous studies show that the correlation structure between test statistics increases the variance and bias of FDR. The objective of this study is to modify the effect of correlation in MCPs based on the information theory. We proposed three modified procedures (M1, M2, and M3) under strong, moderate, and mild assumptions based on the conditional Fisher Information of the consecutive sorted test statistics for controlling the false discovery rate under arbitrary correlation structure. The performance of the proposed procedures was compared with the Benjamini–Hochberg (BH) and Benjamini–Yekutieli (BY) procedures in simulation study and real high-dimensional data of colorectal cancer gene expressions. In the simulation study, we generated 1000 differential multivariate Gaussian features with different levels of the correlation structure and screened the significance features by the FDR controlling procedures, with strong control on the Family Wise Error Rates. Results When there was no correlation between 1000 simulated features, the performance of the BH procedure was similar to the three proposed procedures. In low to medium correlation structures the BY procedure is too conservative. The BH procedure is too liberal, and the mean number of screened features was constant at the different levels of the correlation between features. The mean number of screened features by proposed procedures was between BY and BH procedures and reduced when the correlations increased. Where the features are highly correlated the number of screened features by proposed procedures reached the Bonferroni (BF) procedure, as expected. In real data analysis the BY, BH, M1, M2, and M3 procedures were done to screen gene expressions of colorectal cancer. To fit a predictive model based on the screened features the Efficient Bayesian Logistic Regression (EBLR) model was used. The fitted EBLR models based on the screened features by M1 and M2 procedures have minimum entropies and are more efficient than BY and BH procedures. Conclusion The modified proposed procedures based on information theory, are much more flexible than BH and BY procedures for the amount of correlation between test statistics. The modified procedures avoided screening the non-informative features and so the number of screened features reduced with the increase in the level of correlation