Search Results (828)

Objectives: During cardiac magnetic resonance imaging (cMRI) exams in patients with congenital heart disease (CHD), incidental liver abnormalities are increasingly found. However, no systematic data exist on the incidence of liver lesions in patients with different CHDs. In order to gain a first overview, we retrospectively analyzed cMRI examinations from the last 10 years at our institution. Methods: CMRI examinations including T2-weighted images covering parts of the liver were performed on 899 patients with CHD at our institution between 2014 and 2024. The cMRI examinations were analyzed by a medical student, a pediatrician, a radiologist, and a pediatric cardiologist. Liver lesions were defined as atypical liver parenchyma, showing T2 hyper- or hypointensity compared to the surrounding liver tissue. Results: Liver lesions were found in 9.5% (85/899) of all cMRI studies; of these, 89% ((76/85) of cases) were unknown at time of cMRI, 96% (82/85) were T2 hyperintense, and 38% (32/85) were larger than 1 cm. The patients with liver lesions were older (29 years vs. 22 years, p < 0.0001). There were no sex differences in the incidence of liver lesions or differences in right or left ventricular function (LVEF: 57% vs. 58%, p = 0.78; RVEF: 55% vs. 54%, p = 0.35). The patients with univentricular hearts, transposition of great arteries after atrial switch operation, and atrial septal defects showed the highest incidence (18%, 17%, and 21%, respectively). However, 9% of patients with left heart-sided valve disease also showed liver lesions. Conclusions: Incidental findings of liver lesions in cMRI examinations of patients with CHD are reasonably high with almost 10%. In the growing population of adults with CHD, liver monitoring might be helpful to assure overall patient health. Full article

Automated Short Answer Grading (ASAG) has garnered significant attention in the field of educational technology due to its potential to improve the efficiency, scalability, and consistency of student assessments. This study introduces a novel dataset of 651 student responses from a Database Transaction course exam at Beni-Suef University, referred to as the Beni-Suef Transaction Processing (BeSTraP) dataset. The BeSTraP is specifically designed to support ASAG evaluation. To assess ASAG performance, five approaches were employed: string-based similarity, semantic similarity, a hybrid of both, fine-tuning transformer-based models, and the application of Large Language Models (LLMs). The experimental results indicated that fine-tuned transformers, particularly GPT-2, achieved the highest Pearson correlation with human scores (0.8813) on the new dataset and maintained robust performance on the Mohler benchmark (0.7834). In addition to grading, the framework integrates automated feedback generation through LLMs, further enriching the assessment process. This research contributes (i) a novel, domain-specific dataset derived from an actual university examination, (ii) a comprehensive comparison of traditional and transformer-based approaches, and (iii) evidence of the efficacy of fine-tuned models in providing accurate and scalable grading solutions. The created dataset will be publicly available for the community. Full article

Background/Objectives: Glaucoma is a leading cause of irreversible blindness worldwide, making accurate and efficient detection methods essential. One primary concern with glaucoma is that it often presents no early symptoms. Vision loss typically begins at the periphery and progresses unnoticed until it significantly affects central vision. Due to this gradual and usually silent progression, early detection through regular eye exams is vital for preventing permanent vision loss. Methods: In this study, we propose a hybrid attention mechanism that recalibrates feature maps from the feature extractor for glaucoma detection. We explored normalization-free ResNet (NF-ResNet) architectures to evaluate the proposed attention mechanism, specifically NF-ResNet-26, NF-ResNet-50, and NF-ResNet-101, in comparison to baseline state-of-the-art ResNet variants. Our approach was evaluated on three publicly available glaucoma datasets, LAG, EyePACS, and BrG, to differentiate between normal and glaucomatous from fundus images. Results: The experimental results demonstrate that our proposed hybrid attention module, combined with normalization-free architectures, significantly enhances performance compared to state-of-the-art ResNet variants. The proposed attention model based on the normalization-free ResNet-50 achieved an accuracy of 0.9394 on the LAG dataset, 0.9117 on the EyePACS dataset, and 0.9020 on the BrG dataset. When evaluated on the combined dataset, the model achieved an accuracy of 0.9193, sensitivity of 0.9182, and specificity of 0.9202. Conclusions: The results from these representative datasets for glaucoma detection highlight the exceptional performance of our attention module, establishing it as a highly competitive classification model in the field of glaucoma detection. Full article

Background and Purpose: Neurology requires integration of clinical reasoning, imaging interpretation, and current knowledge, making it an ideal field for evaluating large language models (LLMs). Methods: Using 1715 questions from the Taiwan Neurology Board Examination (2018–2024), we assessed four LLMs—GPT-4o, GPT-o1, DeepSeek-V3, and DeepSeek-R1—across four formats: single-choice, multiple-choice, true–false, and image-based items. Results: GPT-o1 achieved the highest overall accuracy (83.86%) and demonstrated strong performance on cognitively demanding tasks (82.50% on true–false; 77.26% on image-based). DeepSeek-V3 scored lowest (65.62%) and showed the greatest variability. Statistical analyses confirmed significant inter-model differences (p < 0.01). Accuracy declined across all models in 2024, coinciding with shifts in question design. DeepSeek-R1 was further penalized by alignment-based refusals, resulting in up to 3.81% score loss. Conclusions: These results position the Taiwan Neurology Board Exam as a rigorous benchmark for LLM evaluation and underscore GPT-o1’s potential utility in neurology education and decision support. Full article

This study examines the factors driving perceived Study Efficiency and Exam Readiness associated with ChatGPT use among STEM students in higher education. Although prior research on generative artificial intelligence (GenAI) has largely focused on adoption and attitudes using descriptive or linear statistical approaches, limited empirical work has explored how students’ interactions with such tools relate to learning-related outcomes. To address this gap, this study applies an interpretable machine learning (ML) framework to identify key predictors of learning gains from ChatGPT use. Data were obtained from a large-scale global survey of STEM students (n = 10,525) across 109 countries and territories, capturing usage patterns, perceived capabilities, satisfaction, and academic outcomes. Two eXtreme Gradient Boosting (XGBoost)-based ML classification models were developed to predict Study Efficiency and Exam Readiness, and SHapley Additive exPlanations (SHAP) were used to interpret feature-level contributions. The models achieved strong predictive performance for the high-gain class, with an accuracy of 0.93 (F1 = 0.96) for Study Efficiency and 0.86 (F1 = 0.92) for Exam Readiness. Results indicate that motivation, personalized learning support, improved access to knowledge, facilitation of study activities, and exam-focused study assistance are key predictors of learning gains. These findings offer empirical and practical insights for educators and policymakers seeking to design effective and pedagogically sound AI-assisted learning environments in STEM education. Full article

Background/Objectives: Nutritional medicine remains underrepresented in medical education despite its relevance across specialties. Online learning offers a resource-efficient option to address this gap, yet evidence on the effectiveness and acceptability of online learning modules (OLMs) is limited. Methods: In this exploratory randomized controlled single post-test trial, medical students were assigned to either an OLM or an in-person lecture (IPL) on nutritional medicine (n = 91, no a priori sample size calculation performed). After course completion, students took a knowledge test and completed a questionnaire on their learning experience. Group differences were analyzed using permutation Welch t-tests, Wilcoxon–Mann–Whitney tests, or Fisher’s exact tests, depending on variable characteristics, with α = 0.05. Results: OLM students achieved significantly higher test scores than IPL students (mean difference: 2.4 points on a 0–40 scale), resulting in differences in grade classification (p < 0.05). OLM was further rated more favorably regarding content delivery, overall course evaluation, and exam preparation (all p < 0.05), while self-reported attention, concentration, and involvement did not differ between groups. Flexibility, time savings, and convenience were the most frequently reported advantages of OLM over IPL. Conclusions: This study suggests that OLM in nutritional medicine may be associated with higher test performance and more favorable student evaluations compared to IPL. These findings highlight the potential of online learning as a scalable, resource-efficient approach that may help address persistent gaps in nutritional medicine education. Building on this evidence, future work should examine how such modules can be optimally integrated into medical curricula to complement existing teaching structures. Full article

Background: Sudden cardiac death (SCD) and sudden cardiac arrest (SCA) remain leading causes of mortality in young athletes, highlighting the importance of cardiac screening prior to play. The guidelines on screening protocol are continually evolving but are often inconsistent across organizations. We explore the role of different screening modalities including electrocardiography (ECG) and various cardiac imaging testing; their effectiveness, cost considerations and clinical utility regarding sports cardiac screening, comparing European and American cardiac screening protocols. Additionally, we also discuss the divergence between the European and American guidelines and appraise the literature surrounding this topic. Methods: A comprehensive literature review was conducted using studies published between 2010–2025 on cardiac screening for young athletes. Parameters included an English filter with review of observational studies, systematic reviews, meta-analyses, and randomized controlled trials (RCTs). Manual searches of PubMed, Embase, and Google Scholar libraries were also performed to enhance the reach of our investigation. Articles were chosen based on relevance to the topic. Results: When compared to PPCS physical exam, ECG advantages include increased detection of cardiac conditions leading to SCD, improved sensitivity and specificity compared to history alone, Disadvantages are the need for trained specialists to complete testing properly, unreliability for detecting congenital coronary anomalies, cost-effectiveness concerns, and false positive risk. However, these disadvantages can be improved with improved ECG interpretation training for non-cardiologists and policies easing access to advanced cardiac care. Conclusions: ECG remains the cornerstone of cardiovascular screening due to its affordability and sensitivity in detecting electrical abnormalities, its limitations necessitate a multimodal approach. Integrating targeted ECG screening with echocardiography and advanced imaging in select cases may enhance diagnostic accuracy while balancing cost-effectiveness and accessibility. While the benefits of routine ECG are strongly supported by the literature, nationwide implementation of it remains challenging due to economic, geographical and logistical restraints. Therefore, more research needs to be conducted on the mortality benefits and cost-effectiveness of routine ECGs implementation in PPCS screening for young athletes. Full article

University admission exams can be understood as information systems in which subject areas act as components intended to convey predictive signals about students’ future academic performance. However, the informational effectiveness of these subject areas is rarely evaluated using data-driven approaches. This study proposes a data-driven framework for assessing the informational effectiveness of admission exam subject areas by analyzing their empirical relationships with subsequent academic performance. Institutional data of 2197 students across 33 undergraduate programs from two cohorts after four semesters of study are used. Each academic program is represented as a vector of correlations linking performance in admission subject areas to long-term academic outcomes. The importance of each subject area in the admission exam is contrasted with empirically observed correlations to identify mismatches in informational effectiveness. Additionally, similarity analysis is applied to uncover affinities among academic programs. The results reveal substantial heterogeneity in the informational effectiveness of admission exam subject areas, indicating that predefined subject-area weightings do not consistently reflect their empirical contribution. Similarity patterns further identify groups of programs, suggesting opportunities for program-specific optimization of admission exam design. The proposed framework provides a replicable approach for evaluating and refining admission exams as information systems, contributing to data-driven decision-making in educational assessment design. Full article

Background/Objectives: Radiotherapy can severely impair skin and soft tissue healing, particularly when high doses or subsequent surgical interventions are involved. Robust experimental platforms that replicate clinically relevant radiation-impaired wound healing remain limited. This study aims to establish a reproducible experimental model for radiation-induced cutaneous injury using contemporary clinical radiotherapy techniques. Methods: A Wistar rat model was developed using single-dose external beam irradiation delivered by clinical-grade volumetric modulated arc therapy (VMAT; 6 MV FFF), at doses of 20 Gy or 30 Gy. Animals were distributed in five distinct groups: G1—control, G2—20 Gy irradiation only, G3—20 Gy irradiation followed by excision, G4—excision only, G5—30 Gy irradiation only. Standardized full-thickness skin excision (1.5 × 1.5 cm) was performed one-week post-irradiation to simulate surgical intervention in pre-irradiated tissue. Animals were monitored for up to 42 days, through skin damage macroscopic scoring, body weight, hematological and biochemical parameters, and a qualitative histological exam. Results: Single-dose irradiation with 20 Gy induced moderate, self-limiting radiation dermatitis with complete healing. When combined with delayed excision, 20 Gy irradiation resulted in more severe and prolonged wound healing impairment, and transient systemic alterations. Excision alone produced controlled wounds with predictable healing. Exploratory observations following 30 Gy irradiation revealed severe cutaneous injury and marked systemic involvement, with a high mortality rate. Conclusions: This study establishes a foundational model for radiation-impaired wound healing using clinical-grade VMAT delivery and standardized delayed excision. The 20 Gy-based protocols provide an ethically sustainable and experimentally tractable platform for future mechanistic and therapeutic studies. Full article

Background: Chronic noncommunicable diseases account for nearly 80% of global deaths and are strongly associated with insulin resistance (IR). One of the most significant clinical findings of the past two decades is that the molecular mechanisms underlying immune and metabolic systems have been evolutionarily conserved across species. Methods: This study included 34 volunteers (19 men and 15 women). Demographic data were collected using validated questionnaires. Anthropometric measurements (weight, height, waist-to-hip ratio, and body composition assessed by tetrapolar bioimpedance) were obtained directly. Laboratory analyses included fasting glucose and insulin, glycated hemoglobin, HDL cholesterol, total cholesterol, triglycerides, organic aciduria, and additional biochemical markers assessed using standard methods. Group comparisons were performed using parametric or nonparametric statistical tests according to data distribution, as specified in the figure legends. Results: The primary analyses focused on identifying early metabolomic alterations associated with insulin resistance in individuals whose conventional biochemical parameters were within laboratory reference ranges. Individuals with a TG/HDL ratio > 2 and increased urinary kynurenate excretion exhibited a 3.6-fold higher relative risk of insulin resistance, while elevated insulin levels combined with urinary α-ketoisovalerate were associated with a 2.7-fold increased risk. Significant differences in plasma insulin, HbA1c, and HOMA-IR were observed between healthy and diseased individuals (p < 0.05), indicating early metabolic dysfunction preceding clinical disease onset. Conclusions: Metabolomic biomarkers serve as reliable indicators of subclinical metabolic disturbances, revealing significant risks in major metabolic pathways even in individuals with conventional exams within normal limits. Early detection through these metabolomic markers may enable personalized interventions aimed at preserving cellular function and systemic metabolic balance. Full article

Background/Objectives: Adequate bowel preparation (BP) is crucial for effective colorectal cancer (CRC) surveillance in ulcerative colitis (UC). While active inflammation is known to negatively impact cleansing, data regarding predictors of BP quality specifically in UC patients with inactive disease remain limited. This study aimed to investigate risk factors for inadequate BP in UC patients in clinical/endoscopic remission and to compare the efficacy of 1L-PEG-ASC versus 2L-PEG regimens. Methods: A multicentric, retrospective, cohort study was conducted across eight Italian centers. Consecutive adult outpatients with UC undergoing colonoscopy between January-2021 and December-2022 who were in endoscopic and clinical remission were included. Boston Bowel Preparation Scale (BBPS) was assessed in patients undergoing 1L-PEG-ASC or 2L-PEG bowel preparation. Univariable and multivariable logistic regression analyses were performed to identify risk factors for inadequate BP and compare outcomes between PEG regimens. Results: A total of 379 patients were included (58% M, mean age 52.3 ± 15.4 years). The overall rate of adequate BP was 90.5%. Traditional risk factors, including demographic, clinical, and endoscopic characteristics, were not predictive of inadequate preparation in this remission cohort. Comparing regimens, 1L-PEG-ASC yielded significantly higher median total BBPS scores compared to 2L-PEG (8 [IQR 7–9] vs. 6 [IQR 6–8]; p < 0.001) and a higher exam completion rate (99.5% vs. 95.7%; p = 0.02), although the difference in adequate BP rates did not reach statistical significance (92.6% vs. 87.7%; p = 0.12). Multivariable analysis confirmed that 2L-PEG was independently associated with lower odds of achieving higher BBPS scores (OR 0.30; 95% CI 0.20–0.45). Conclusions: In UC patients with clinical and endoscopic remission, BP adequacy rates are high and comparable to the general population, suggesting that traditional IBD-related risk factors are less relevant in the absence of active inflammation. However, the 1L-PEG-ASC regimen demonstrated superior cleansing quality and exam completion rates compared to 2L-PEG. These findings support the prioritization of 1L-PEG-ASC to optimize mucosal visualization during CRC surveillance in this population. Full article

Examinations are central to higher education, yet students consistently describe them as detrimental to well-being. Drawing on self-determination theory (SDT), we conducted three studies to examine whether multiple-choice examinations could be redesigned to satisfy students’ basic psychological needs (BPNs) and support well-being. In Study 1 (n = 400), we developed and validated the Basic Psychological Need Satisfaction and Frustration Scale for Classroom Assessment (BPNSF-CA). Using bifactor exploratory structural equation modeling (bifactor ESEM), results supported a well-defined single global need fulfillment factor (G-factor) alongside six specific factors (autonomy support/frustration, competence support/frustration, relatedness support/frustration) as well as evidence of validity. In Study 2 (n = 387), we conducted a randomized experiment with three versions of a multiple-choice exam serving as the independent variable (flawed items, high-quality items, and high-quality + need-supportive features). Results showed that high-quality items improved performance, while only the addition of need-supportive features satisfied BPNs with differential patterns for the single G-factor and S-factors. In Study 3 (n = 101), we applied the intervention in a real classroom and tested the mediational role of BPN satisfaction. Results showed that redesigned exams (high-quality + need-supportive features) significantly enhanced perceptions of fairness and success via BPNs. We conclude with a discussion of all three studies, including implications and limitations. Full article

Objective: We evaluate the performance and relevance of MRI to detect csPC in men with normal PSA. Methods: Out of our database of patients referred for prostate MRI, we selected men with PSA < 4 ng/mL for whom histopathology or at least 2 years of clinical follow-up data were available as standard of reference. Subgroup analyses were performed for the patients with PSA < 3 ng/mL, <2 ng/mL, and 2–3.9 ng/mL. The reasons for prostate MRI referral despite their normal PSA level were retrieved by exploring the patients’ files. The prostate MRIs were reported according to the Prostate Imaging and Reporting Data System (PI-RADS), and the overall assessment score was registered. For evaluation of the performance, PI-RADS ≥ 3 was set as a threshold for a positive exam. The patients without PC or only International Society of Urological Pathology (ISUP) grade group 1 PC (Gleason 3+3) were considered as one category having no csPC. The performance of prostate MRI was separately evaluated for detection of ISUP ≥ 2 and for ISUP ≥ 3 csPC. Results: A total of 148 men were included, with PSA ranging from 0.42 to 3.99 ng/mL (median 2.95, IQR 1.68–3.50) and age ranging from 36 to 84 years (median 58, IQR 52–66). A total of 74 men (50.0%) had a PSA level < 3 ng/mL, 42 (28.4%) had a PSA level < 2 ng/mL, and 106 (71.6%) had a PSA level of 2–3.9 ng/mL. They were referred for prostate MRI for a wide variety, and usually a combination of, reasons, such as younger age (<60 years in 55.4%, N = 82; <50 years in 17.6%, N = 26), abnormal digital rectal examination in 31.8% of cases (N = 47), suspicious PSA dynamics in 29.7% (N = 44), positive familial history in 27.0% (N = 40), clinical signs of prostatitis in 18.2% (N = 27), suspicious findings on Transrectal Ultrasound (TRUS) in 16.9% (N = 25), hematospermia in 7.4% (N = 11), hematuria in 4.1% (N = 6), incidental hot spot in the prostate on Fluoro-Deoxy-Glucose (FDG) Positron Emission Tomography (PET)–Computed Tomography (CT) in 4.1% (N = 6), lymphadenopathies on CT in 2.7% (N = 4), or severe patient anxiety in 3.4% (N = 5). Overall, ISUP ≥ 2 PC was present in 18.9% (N = 28) of cases, and MRI detected this with a sensitivity of 92.9%, a specificity of 66.7%, and a positive predictive value of 39.4%. ISUP ≥ 3 PC was present in 9.5% (N = 14) of cases, and prostate MRI detected this with a sensitivity of 100%, a specificity of 61.2%, and a positive predictive value of 21.2%. In patients with PSA < 2 ng/mL (N = 42), no csPC was found, but MRI generated false positives in 33.3%. Conclusions: Performing prostate MRI in men with normal PSA (<4 ng/mL) seems useful if there are other reasons that increase the clinical suspicion of csPC. In about one-fifth of these patients, csPC is present and MRI has high sensitivity for its detection. Prostate MRI has, however, low positive predictive value in this patient group, and clinicians should be aware of the risk of false-positive MRI. Below a PSA level of 2 ng/mL, no csPC was found and prostate MRI generated only false positives, suggesting limited value in this subgroup. Full article

Objective: This study aimed to compare the accuracy of two large language models (LLMs)—ChatGPT (version 3.5) and Google Gemini (formerly Bard)—in answering dental caries-related multiple-choice questions (MCQs) using a simulated student examination framework across seven examination lengths. Materials and Methods: A total of 125 validated dental caries MCQs were extracted from Dental Decks and Oxford University Press question banks. Seven examination groups were constructed with varying question counts (25, 35, 45, 55, 65, 75, and 85 questions). For each group, 100 simulations were generated per LLM (ChatGPT and Gemini), resulting in 1400 simulated examinations. Each simulated student received a unique randomized subset of questions. MCQs were answered by each LLM using a standardized prompt to minimize ambiguity. Outcomes included mean score, passing rate (≥60%), and performance differences between LLMs. Statistical analyses included independent t-tests, one-way ANOVA within each LLM, and two-way ANOVA examining interactions between LLM type and question count. Results: Across all seven examination formats, Gemini significantly outperformed ChatGPT (p < 0.001). Gemini achieved higher passing rates and higher mean scores in every examination length. One-way ANOVA revealed significant score variation with increasing exam length for both LLMs (p < 0.05). Two-way ANOVA demonstrated significant main effects of LLM type and question count, with no significant interaction. Randomization had no measurable effect on Gemini performance but influenced ChatGPT scores. Conclusions: Gemini demonstrated superior accuracy and higher passing rates compared to ChatGPT in all simulated examination formats. While both LLMs struggled with complex caries-related content, Gemini provided more reliable performance across question quantities. Educators should exercise caution in relying on LLMs for automated assessment or self-study, and future research should evaluate human–AI hybrid models and LLM performance across broader dental domains. Full article

Background: Pulmonary infarction (PI) is the result of the occlusion of distal pulmonary arteries resulting in damage to downstream lung areas that become ischemic, hemorrhagic, or necrotic, and it is often a complication of an underlying condition such as pulmonary embolism (PE). Since in most of cases it is located peripherally, lung ultrasound (LUS) can be a good evaluation tool. The typical radiological features of PI are well-known; however, there are limited data on its sonographic characteristics and its evolution. Methods: The aim of this study is to evaluate, using LUS, a convenience sample of patients with acute PE with computed tomography (CT) consolidation findings consistent with PI. Patients’ clinical characteristics were collected and LUS findings at baseline and their short-term progression was assessed. LUS was performed within 72 h of PE diagnosis (T0) and repeated after one (T1) and four weeks (T2). Each procedure started with a focused examination of the areas of lesions based on CT findings, followed by an exploration of the other posterior and lateral lung fields. The convex probe was used for initial evaluation integrating LUS evaluation with the linear one was employed for smaller and more superficial lesions and when appropriate. Color Doppler mode was added to study vascularization. Results: From June to October 2023, 14 consecutive patients were enrolled at the Respiratory Unit of the University Hospital of Pisa. The main population characteristics included the absence of respiratory failure and prognostic high-risk PE (100%), the absence of significant comorbidities (79%), and the presence of typical symptoms, such as chest pain (57%) and dyspnea (50%). The average number of consolidations per patient was 1.4 ± 0.6. Follow-up LUS showed the disappearance of some consolidations and some morphological changes in the remaining lesions: the presence of hypoechoic consolidation with a central hyperechoic area (“bubbly consolidation”) was more typical at T1 while the presence of a small pleural effusion often persisted both at T1 and T2. A decrease in wedge/triangular-shaped consolidations was observed (82% at T0, 67% at T1, 24% at T2), as was an increase in elongated shapes, representing a residual pleural thickening over time (9% at T0, 13% at T1, 44% at T2). A reduction in size was also observed by comparing the mean diameter, long axis, and short axis measurements of each consolidation at the three different studied time points: the average of the short axes and the median of the mean diameters showed a statistically significant reduction after four weeks. Additionally, a correlation between lesion size and pleuritic pain was described, although it did not achieve statistical significance. Conclusions: Patients’ clinical characteristics and ultrasound features are consistent with previous studies studying PI at PE diagnosis. Most consolidations detected by LUS change over time regarding size and form, but a minority of them do not differ. LUS is a safe and non-invasive exam that could help to improve patients’ clinical approach in emergency rooms as well as medical and pulmonology settings, clinically contextualized for cases of chest pain and dyspnea. Future studies could expand the morphological study of PI. Full article