A Comparative Study of Sentiment Analysis Methods for Detecting Fake Reviews in E-Commerce

Evaluations of early screening tests for autism commonly rely on receiver operating characteristic (ROC) analysis and comparisons of area under the curve (AUC). Whether AUC differs significantly from chance or between test items is not always assessed. Two recent and independent evaluations of the Brief Autism Detection in Early Childhood (BADEC) constructed a short-form by selecting the five items with the highest AUC values, leading to inconsistencies regarding appropriate item content (Nah et al., 2018; Nevill et al., 2019). Using significance testing to compare AUC values for each test item from each dataset, we demonstrate which items justify inclusion in the BADEC, which items can be ruled out, and highlight key factors influencing AUC significance testing outcomes.

Frailty, a decline in physical and cognitive reserve capacity, renders patients susceptible to various stressors and has been linked to adverse outcomes and increased healthcare utilization. This study aimed to determine whether ultrasound measurements of the rectus abdominis (RA) and biceps brachii (BB) could predict frailty in patients scheduled for total knee arthroplasty. Frailty was assessed using the Clinical Frailty Scale in adults aged ≥60 years. Ultrasound measurements of the rectus abdominis, BB, and quadriceps femoris muscles, along with thigh circumference measurements, were obtained before surgery. The predictive ability of the unadjusted and BMI- and body surface area (BSA)-adjusted measurements were evaluated using receiver operating characteristic curve analysis and area under the curve (AUC) values. Postoperative outcomes, such as admission to the intensive care unit or skilled nursing facility, delirium, falls, re-hospitalization, and 30-day mortality were recorded. We analyzed data from 148 patients. BB thickness provided a fair prediction of frailty. Average measurements of both BB adjusted for BMI (0.708, 95% CI 0.602-0.814; P<0.001), and BSA (0.708, 95% CI 0.598-0.817; P<0.001) had the highest AUC values. RA muscle measurements could not discriminate frailty. The BMI-adjusted measurements for: right quadriceps femoris thickness (AUC 0.614, 95% CI 0.503-0.725; P=0.044), left thigh circumference (AUC 0.648, 95% CI 0.528-0.769; P=0.016), and average thigh circumference (AUC 0.630, 95% CI 0.511-0.750; P=0.033) had statistically significant but poor AUC values. Preoperative ultrasound measurements of the bilateral BB can fairly predict frailty in patients scheduled for total knee arthroplasty.

Background/aimsTo evaluate the predictive performance of various predictors, including non-cycloplegic refractive error, for risk of myopia onset under pragmatic settings.MethodsThe Wenzhou Medical University Essilor Progression and Onset of Myopia Study...

BackgroundTo examine the influence of voxel sizes to detect of peri-implant fenestration defects on cone beam computed tomography (CBCT) images.Materials and methodsThis study performed with three sheep heads both maxilla and mandible and two types of dental implant type 1 zirconium implant (Zr40) (n = 6) and type 2 titanium implant (Ti22) (n = 10). A total of 14 peri-implant fenestrations (8 buccal surfaces, 6 palatal/lingual surface) were created while 18 surfaces (8 buccal, 10 palatal/lingual) were free of fenestrations. Three observers have evaluated the images of fenestration at each site. Images obtained with 0.75 mm3, 0.100 mm3, 0.150 mm3, 0.200 mm3, and 0.400 mm3 voxel sizes. For intra- and inter-observer agreements for each voxel size, Kappa coefficients were calculated.ResultsIntra- and inter-observer kappa values were the highest for 0.150 mm3, and the lowest in 0.75 mm3 and 0.400 mm3 voxel sizes for all types of implants. The highest area under the curve (AUC) values were found higher for the scan mode of 0.150 mm3, whereas lower AUC values were found for the voxel size for 0.400 mm3. Titanium implants had higher AUC values than zirconium with the statistical significance for all voxel sizes (p ≤ 0.05).ConclusionA voxel size of 0.150 mm3 can be used to detect peri-implant fenestration bone defects. CBCT is the most reliable diagnostic tool for peri-implant fenestration bone defects.

ObjectiveTo explore potential functional biomarkers in diabetes mellitus (DM) by utilizing gene pathway cross-talk.MethodsFirstly, potential disrupted pathways that were enriched by differentially expressed genes (DEGs) were identified based on biological pathways downloaded from the Ingenuity Pathways Analysis (IPA) database. In addition, we quantified the pathway crosstalk for each pair of pathways based on Discriminating Score (DS). Random forest (RF) classification was then employed to find the top 10 pairs of pathways with a high area under the curve (AUC) value between DM samples versus normal samples based on 10-fold cross-validation. Finally, a Monte Carlo Cross-Validation was applied to demonstrate the identified pairs of pathways by a mutual information analysis.ResultsA total of 247 DEGs in normal and disease samples were identified. Based on the F-test, 50 disrupted pathways were obtained with false discovery rate (FDR) &lt; 0.01. Simultaneously, after calculating the DS, the top 10 pairs of pathways were selected based on a higher AUC value as measured by RF classification. From the Monte Carlo Cross-Validation, we considered the top 10 pairs of pathways with higher AUC values ranked for all 50 bootstraps as the most frequently detected ones.ConclusionThe pairs of pathways identified in our study might be key regulators in DM.

Impacts of consumer cognitive process to ascertain online fake review: A cognitive dissonance theory approach

BackgroundTo improve the diagnostic performance of the cerebrospinal fluid (CSF) tap test (TT), early and delayed assessments of gait were performed after the removal of 30 ml of CSF in patients with probable idiopathic normal pressure hydrocephalus. Assessments of gait included the 3-m timed up and go test (TUG), and the 10-m walk in time (10Ti) and in step (10St) tests.MethodsQuantitative data for the TUG, the 10Ti, and the 10St were obtained before CSF removal and on days 1 and 4 after removal of 30 ml CSF. CSF shunt surgery was performed in 61 patients within one month after the TT. The gait outcome was assessed 3 months after surgery. The area under the curve (AUC), sensitivity, specificity, and cutoff values were computed for the TUG, the 10Ti, and the 10St on day 1 and day 4 using receiver operating characteristic (ROC) curve analysis.ResultsThe positive response rate in three measures on day 4 was equal to or higher than the values on day 1. Times were reduced significantly in the TUG and the 10mTi tests between baseline and both days 1 and 4 after TT. No significant differences were noted in the number of steps for the 10St test. The percent change in TUG on day 1 had the highest AUC value among all other variables (0.808). Although this was not statistically different from other variables in the TUG and the 10Ti, it had a good balance of high sensitivity (78.3%) and high specificity (80.0%), with a cutoff value of 11.3%. The change in the measured value in the day 1 TUG had the second highest AUC value at 0.770. The variables on day 4 tended to have high specificities of around 90%, although their sensitivities were low.ConclusionsThe percent change of TUG on day 1 showed the highest diagnostic accuracy. Delayed assessments on day 4 were not superior to those on day 1. Thus, the TUG on day 1 is useful as a simple quantitative measure for predicting shunt effectiveness.

To translate, culturally adapt, and validate the psychometric characteristics of the Italian version of the Dance Functional Outcome Survey (DFOS-IT) in adult dancers. Clinical measurement study. The DFOS-IT was forward translated, reconciled, backward translated, and reviewed by an expert committee to establish optimal correspondence with the original English DFOS. We examined test-retest reliability in 58 dancers within a 10-day period, using intraclass correlation coefficients (ICC2,1). In a sample of 265 healthy and injured dancers, the following were examined: 1) construct validity, comparing the DFOS-IT to SF-36 using Pearson correlations; 2) exploratory factor analysis and internal consistency; and 3) sensitivity, by generating receiver operating characteristic curves and determining area under the curve (AUC). In a subgroup of 44 dancers, we determined internal responsiveness across three time-points using repeated measures ANOVA (p<0.05). Injured dancers' scores were analyzed for floor and ceiling effects. The DFOS-IT demonstrated very high test-retest reliability (ICC≥0.98). Single-factor loading in exploratory factor analysis supported unidimensionality of the scale, with high internal consistency (a=0.93). DFOS-IT total, activities of daily living (ADL), and Dance Technique scores had strong construct validity compared with scores on the SF-36 PCS (r≥0.71). There was excellent sensitivity, with high AUC values (AUC≥0.80). There were significant differences across time for DFOS-IT scores (p<0.001), demonstrating responsiveness to change, and no floor or ceiling effects. The DFOS-IT is a valid, reliable, and responsive tool that can be used as an outcome and screening measure for Italian adult ballet and modern dancers following lower extremity or low back injury.

IntroductionAs one of the most prevalent chronic diseases in the United States, diabetes, especially type 2 diabetes, affects the health of millions of people and puts an enormous financial burden on the US economy. We aimed to develop predictive models to identify risk factors for type 2 diabetes, which could help facilitate early diagnosis and intervention and also reduce medical costs.MethodsWe analyzed cross-sectional data on 138,146 participants, including 20,467 with type 2 diabetes, from the 2014 Behavioral Risk Factor Surveillance System. We built several machine learning models for predicting type 2 diabetes, including support vector machine, decision tree, logistic regression, random forest, neural network, and Gaussian Naive Bayes classifiers. We used univariable and multivariable weighted logistic regression models to investigate the associations of potential risk factors with type 2 diabetes.ResultsAll predictive models for type 2 diabetes achieved a high area under the curve (AUC), ranging from 0.7182 to 0.7949. Although the neural network model had the highest accuracy (82.4%), specificity (90.2%), and AUC (0.7949), the decision tree model had the highest sensitivity (51.6%) for type 2 diabetes. We found that people who slept 9 or more hours per day (adjusted odds ratio [aOR] = 1.13, 95% confidence interval [CI], 1.03–1.25) or had checkup frequency of less than 1 year (aOR = 2.31, 95% CI, 1.86–2.85) had higher risk for type 2 diabetes.ConclusionOf the 8 predictive models, the neural network model gave the best model performance with the highest AUC value; however, the decision tree model is preferred for initial screening for type 2 diabetes because it had the highest sensitivity and, therefore, detection rate. We confirmed previously reported risk factors and also identified sleeping time and frequency of checkup as 2 new potential risk factors related to type 2 diabetes.

Evaluation of Lung Toxicity Risk with Computed Tomography Ventilation Functional Image for Lung Stereotactic Body Radiation Therapy and Three-Dimensional Conformal Radiation Therapy

Use of A Systemic Inflammatory Response Index to Predict Non-Traumatic Non-Aneurysmal Subarachnoid Hemorrhage Patient Outcomes

Purpose: The aim of our study is to investigate the prognostic value of Neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and platelet-to-lymphocyte ratio (PLR) in determining mortality in patients hospitalized for intensive care unit (ICU) sepsis. Materials and Methods: This study retrospectively evaluates all patients hospitalized with sepsis in our ICU between February 2017 and April 2018. In addition to the demographic and clinical characteristics of the patients, complete blood count parameters were also recorded. Demographic and clinical characteristics, mainly NLR, MLR and PLR results, and other laboratory results of patients with sepsis were compared between the ones with and without mortality. Results: Four hundred and eleven patients were included in the study. 55.7% (229/411) of patients with sepsis died and 44.3% (182/411) were discharged alive. NLR, MLR and PLR were higher in the group with mortality compared to the survivor group. The cut-off value for predicting mortality in patients with sepsis was 9.2 for NLR, ≥0.8 for MLR, and ≥187.3 for PLR. The area under the curve (AUC) value for NLR was 0.825, the AUC value for MLR 0.835 and the AUC value for PLR was 0.720. Conclusion: High NLR, MLR and PLR values are associated with mortality in sepsis patients hospitalized in ICU, and the most significant parameter for mortality indicator among the three rates was found to be MLR with the highest AUC value.

Backgroundβ-synuclein (β-syn), mainly expressed in central nerve system, is one of the biomarkers in cerebrospinal fluid (CSF) and blood for synaptic damage, which has been reported to be elevated in CSF and blood of the patients of prion diseases (PrDs).MethodsWe analyzed 314 CSF samples from patients in China National Surveillance for CJD. The diagnostic groups of the 223 patients with PrDs included sporadic Creutzfeldt-Jacob disease (sCJD), genetic CJD (gCJD), fatal familial insomnia (FFI) and Gerstmann-Straussler-Scheinker (GSS). 91 patients with non-PrDs comprised Alzheimer’s disease (AD), Parkinson's disease (PD), viral encephalitis (VE) or autoimmune encephalitis (AE) were enrolled in the control groups. The CSF β-syn levels were measured by a commercial microfluidic ELISA. The Mann–Whitney U test and Kruskal–Wallis H test were employed to analyze two or more sets of continuous variables. Multiple linear regression was also performed to evaluate the factors for CSF β-syn levels. Receiver operating characteristics (ROC) curves and area under the curve (AUC) values were used to assess the diagnostic performance of β-syn.ResultsThe median of β-syn levels (2074 pg/ml; IQR: 691 to 4332) of all PrDs was significantly higher than that of non-PrDs group (504 pg/ml; IQR: 126 to 3374). The CSF β-syn values in the cohorts of sCJD, T188K-gCJD, E200K-gCJD and P102L-GSS were remarkably higher than that of the group of AD + PD, but similar as that of the group of VE + AE. The elevated CSF β-syn in sCJD and gCJD cases was statistically associated with CSF 14-3-3 positive and appearance of mutism. ROC curve analysis identified satisfied performance for distinguishing from AD + PD, with high AUC values in sCJD (0.7640), T188K-gCJD (0.8489), E200K-gCJD (0.8548), P102L-GSS (0.7689) and D178N-FFI (0.7210), respectively.ConclusionOur data here indicate that CSF β-syn is a potential biomarker for distinguishing PrDs (gCJD, sCJD and GSS) from AD and PD, but is much less efficient from VE and AE. These findings have critical implications for early diagnosis and monitoring of synaptic integrity in prion diseases.

BackgroundNeuroblastoma (NB) is a heterogeneous pediatric malignancy with highly variable outcomes. Traditional clinical factors, such as stage, MYCN status, and patient age, often fail to fully capture disease complexity. Recent advances in single-cell sequencing and integrative transcriptomic analyses provide an opportunity to identify more precise prognostic biomarkers and guide individualized therapies. This study aimed to develop and validate a robust prognostic model for NB by integrating single-cell and bulk transcriptomic data.MethodsWe integrated seven publicly available single-cell RNA sequencing (scRNA-seq) datasets to form the Neuroblastoma Atlas and stratified tumor cells into high-risk and intermediate/low-risk groups. Differentially expressed genes (DEGs) were identified using defined fold-change and expression thresholds. Candidate genes were further validated using bulk RNA-sequencing data (HRA002064) and intersected with essential genes defined by DepMap Computational estimation of gene dependency using Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) screening (CERES) scores. From the resulting set, we constructed a multivariate Cox regression-based prognostic model using the GSE49710 dataset. The model’s performance was evaluated via Kaplan-Meier curves, time-dependent receiver operating characteristic analysis, and decision curve analysis. External validation was performed in the E-MTAB-8248 dataset, and comparisons with standard clinical indicators (International Neuroblastoma Staging System, MYCN status, age) were conducted.ResultsIntegrating scRNA-seq and bulk RNA-seq data identified 123 overlapping DEGs, of which seven genes (BIRC5, CDC2, GINS2, MAD2L1, ORC6L, RRM2, TOP2A) were further prioritized based on CERES dependency scores. Multivariate Cox regression and collinearity screening yielded a four-gene prognostic model (RiskScore) that significantly discriminated high- and low-risk patients in the GSE49710 cohort. Compared to traditional indicators, the four-gene model demonstrated superior time-dependent area under the curve (AUC) values and clinical decision-making benefits. External validation in E-MTAB-8248 confirmed the model’s robust predictive performance, with high AUC values at 1-, 3-, and 5-year time points and consistent superiority over clinical parameters.ConclusionsThis study presents a novel four-gene prognostic signature derived from integrative scRNA-seq and bulk RNA-seq analyses. The model outperforms established clinical factors in predicting NB outcomes and provides added clinical decision-making value. Further prospective validation and mechanistic investigations may facilitate the translation of this prognostic signature into routine clinical practice, enabling more refined risk stratification and personalized treatment strategies for children with NB.

Background/Objectives: Non-variceal upper gastrointestinal bleeding (NVUGIB) remains a major clinical emergency, particularly among patients receiving antiplatelet or anticoagulant therapy, whose use has increased substantially in recent years. This study aimed to evaluate the clinical characteristics, endoscopic findings, risk stratification, and outcomes of NVUGIB in patients receiving antithrombotic therapy, and to compare the predictive performance of commonly used prognostic scores. Methods: This prospective cohort study included 89 patients receiving antithrombotic therapy who presented with NVUGIB at Beni-Suef University Hospitals between March 2023 and March 2025. Clinical presentation, laboratory findings, and endoscopic characteristics were recorded. Risk stratification was assessed using Glasgow-Blatchford (GBS), Rockall, Baylor, AIMS65, ABC, and PNED scores. The optimal cut-off values for prediction of rebleeding and mortality were determined using receiver operating characteristic (ROC) analysis and the Youden index. Area under the curve (AUC) values were reported with 95% confidence intervals. Results: Endoscopy revealed that peptic ulcers were the most common lesion (41/89, 46%), followed by erosive disease (27/89, 30%), with the stomach being the most frequently involved site (76.5%). Rebleeding occurred in 16 patients (18.0%), while mortality was observed in 2 patients (2.2%). The Glasgow-Blatchford score demonstrated the most consistent performance for predicting rebleeding, with an optimal cutoff value of 5.5 (derived using the Youden index), yielding 92.9% sensitivity and 78.8% specificity. For mortality prediction, AIMS65, ABC, and PNED scores showed very high AUC values, although these findings should be interpreted cautiously due to the small number of mortality events (n = 2). No statistically significant difference in rebleeding or mortality was observed between single and dual antithrombotic therapy, although patients receiving dual therapy required longer hospitalization and more transfusion units. Conclusions: In patients with antithrombotic-related GI bleeding, ulcers and erosions predominate, with minimal differences between single and dual therapy outcomes. Concomitant NSAID use trends toward higher mortality. Glasgow-Blatchford score offers optimal performance for both rebleeding and mortality prediction, with a cutoff of 5.5 providing excellent sensitivity (92.9%) and specificity (78.8%) for rebleeding risk assessment.