Search Results (1,183)

Background: Pediatric inflammatory bowel disease (IBD) is characterized by a heterogeneous and often aggressive disease course, requiring complex multimodal assessment and long-term monitoring. Artificial intelligence (AI) has emerged as a promising tool to support clinical decision-making by enabling an objective analysis of large, multidimensional datasets. Objectives: This narrative review aims to critically synthesize current evidence on the application of AI across the diagnosis, monitoring, and treatment of pediatric IBD. Methods: A narrative literature review was conducted using the PubMed (MEDLINE) and Cochrane Library databases, including publications available up to December 2025. Pediatric-focused studies were prioritized. However, due to the limited availability of pediatric-specific AI research, a considerable proportion of the evidence reviewed derives from adult or mixed cohorts, which were included when methodological frameworks or clinically relevant endpoints were applicable to pediatric IBD. Eligible publications included narrative and systematic reviews, observational studies, and clinical trials focusing on AI applications in endoscopy, histology, imaging, disease monitoring, and therapeutic response prediction. Results: AI-based models, particularly those using machine learning and deep learning, demonstrated promising performance in the automated analysis of endoscopic, histological, and imaging data, reducing interobserver variability and improving workflow efficiency. Multimodal approaches integrating imaging, clinical, and biomarker data consistently outperformed unimodal models. Emerging applications in patient-centered monitoring, digital biomarkers, and telemedicine enabled continuous disease assessment and early detection of flares, with particular relevance in pediatric settings where repeated, non-invasive monitoring is essential. AI-driven models also showed promising accuracy in predicting therapeutic response, supporting treatment stratification and precision medicine strategies. Conclusions: AI shows promising potential to complement clinical expertise in pediatric IBD by supporting diagnostic assessment, disease monitoring, and therapeutic optimization. However, translation into routine clinical practice remains constrained by methodological heterogeneity, limited pediatric-specific validation, and unresolved ethical and regulatory challenges. Future research should prioritize prospective multicenter pediatric studies, the development of transparent and explainable models, and the integration of AI-based tools into clinically meaningful and patient-centered care pathways. Full article

To evaluate cross-platform measurement consistency and diagnostic threshold requirements in shear wave elastography (SWE), this study presents a robotically controlled, phantom-based validation framework to quantify and interpret inter-vendor variability that limits clinical standardisation. A custom-fabricated polyvinyl chloride-graphite phantom containing eight spherical inclusions (15–25 mm diameter, 25–95 mm depth, 23.53–259.58 kPa stiffness), representing breast tissue mechanical properties, was evaluated using Samsung HS50 and Aixplorer ultrasound systems. Robotic automation standardised probe positioning and contact, eliminating operator-dependent variability and enabling direct, system-level comparison. Cross-platform reproducibility, accuracy against mechanically validated ground truth, and diagnostic threshold performance were assessed across 80 measurements. Both systems demonstrated excellent intra-machine reproducibility (coefficient of variation: Samsung 0.42%, Aixplorer 0.46%) with strong inter-machine correlation (r = 0.9951, p < 0.0001). However, systematic bias of 7.05 kPa and 95% limits of agreement spanning 38.7 kPa revealed substantial cross-platform measurement differences. All phantom inclusions (8/8) measured below their assigned ground truth stiffness on both systems, with systematic underestimation ranging from 0.33 kPa to 109.57 kPa, indicating parameter-dependent measurement distortion linked to inclusion size, depth, and stiffness. Dynamic range compression was observed (Samsung: 68.7%, Aixplorer: 59.1% of true phantom range), providing a mechanistic explanation for diagnostic threshold instability. This study contributes an interpretable validation methodology that links SWE measurement bias to physical lesion properties and imaging system characteristics, rather than relying on correlation alone. Despite strong reproducibility, the observed system-dependent bias demonstrates that SWE measurements are not directly transferable across ultrasound platforms, and system-specific collaboration is required to ensure reliable clinical interpretation. Full article

Methane is the second most important contributor to global warming, and monitoring super-emitters from space is critical for climate mitigation. Despite the advancements in hyperspectral remote sensing, comparing methane observations across diverse imaging spectrometers remains a challenging task. Different retrieval algorithms, plume segmentation techniques and uncertainty treatments make it very hard to perform fair comparisons between different products. To overcome these difficulties, this study presents HyGAS (Hyperspectral Gas Analysis Suite), a unified, open-source framework for sensor-agnostic methane retrieval and flux estimation. Starting from the established clutter-matched-filter (CMF) formalism and a physical calibration in concentration–path-length units (ppm·m), we propagate both instrument noise and surface-driven background variability consistently from methane enhancement to Integrated Mass Enhancement (IME) and flux. The framework further includes a spectrally matched background-selection strategy, scale-aware segmentation with fixed physical criteria across resolutions, and emission-rate estimation via an IME–U_eff$U_{eff}$ approach informed by Large Eddy Simulation (LES). We demonstrate the framework on near-simultaneous observations of landfills and gas infrastructure in Argentina, Turkmenistan, and Pakistan, spanning Level-1 radiance workflows (PRISMA, EnMAP, Tanager-1) and Level-2 methane products (EMIT, GHGSat). The standardised chain enables systematic inter-comparison of methane enhancement products and reduces methodological bias, supporting robust multi-mission assessment and future global monitoring. Full article

Background/Objectives: Emergency department length of stay (ED LOS) is a key indicator reflecting emergency department crowding, patient safety, and healthcare resource efficiency. Among injured patients, ED LOS may be prolonged depending on injury severity and disposition pathways (admission and inter-hospital transfer). This nationwide study using the Korean National Emergency Department Information System (NEDIS) aimed to (1) describe the distribution and determinants of ED LOS among injured patients and (2) quantify the mediating effects of disposition (admission and transfer) on the association between injury severity measured by the International Classification of Diseases-based Injury Severity Score (ICISS) and ED LOS. Methods: We analyzed NEDIS injury-related ED visit records collected from the date of IRB approval through 12 January 2026. We conducted a retrospective observational study using NEDIS data. Of 1,048,575 injury-related ED visits, 1,035,484 visits with valid ED LOS and eligible records were included after excluding missing key variables and implausible time values. ED LOS was calculated in minutes using arrival and departure timestamps. Injury severity was assessed using ICISS (primary: based on 15 diagnoses; sensitivity: based on 20 diagnoses). Determinants of ED LOS were evaluated using gamma regression with a log link. Disposition was categorized as discharge, admission, and inter-hospital transfer; admission and transfer were modeled as binary mediators. Causal mediation analyses estimated the average causal mediation effect (ACME), average direct effect (ADE), total effect, and proportion mediated. Multiple sensitivity analyses (outlier handling, missing-data approaches, alternative log-linear modeling, and EMS arrival subgroup analyses) assessed robustness. Results: The median ED LOS was 150 min (IQR 90–260). ED LOS differed substantially by disposition: 120 min for discharged patients, 420 min for admitted patients, and 360 min for transferred patients. Overall, 17.9% of visits had an ED LOS ≥ 6 h, and prolonged stays were concentrated among admitted (≥6 h: 55.0%) and transferred (≥6 h: 45.0%) patients. In gamma regression, a 0.05 decrease in ICISS (greater severity) was associated with longer ED LOSs in the unadjusted model (Ratio 1.34) and remained significant in the fully adjusted model (Ratio 1.12, 95% CI 1.11–1.13). Admission and transfer were strong determinants of ED LOS in the final model (ratios of 2.35 and 2.05, respectively). In mediation analyses, admission mediated 36.8% of the severity–ED LOS association (ACME 0.085; ADE 0.146), and transfer mediated 14.3% (ACME 0.033; ADE 0.198). Findings were consistent across sensitivity analyses. Conclusions: In this nationwide cohort of injured patients, ED LOS showed a right-skewed distribution, with prolonged stays concentrated in admission and transfer pathways. Injury severity (ICISS) was independently associated with longer ED LOS, and a substantial proportion of this association was mediated through admission and transfer. Reducing ED LOS among severely injured patients likely requires not only streamlining diagnostic and treatment processes but also system-level interventions targeting output-stage bottlenecks, including inpatient bed operations/boarding management and transfer coordination. Full article

Background and Objectives: Large language models (LLMs) have demonstrated high performance on knowledge-based medical examinations but their capabilities on cognitive aptitude tests emphasizing reasoning and abstraction remain underexplored. The Test for Medical Studies (TMS), a German medical school admission test, provides a standardized framework to examine these capabilities. This study aimed to evaluate the performance and consistency of multiple LLMs on text-based and visual-analytic TMS items. Materials and Methods: Eight contemporary LLMs, comprising proprietary and open-source systems, were evaluated using a multi-run design on standardized TMS items spanning text-based and visual-analytic cognitive domains. Results: Mean accuracy remained substantially below levels typically reported for knowledge-based medical examinations, with marked performance differences between text-based and visual-analytic subtests. Open-source models performed competitively compared with proprietary systems. Inter-run reliability was heterogeneous, indicating notable variability across repeated evaluations. Conclusions: Current LLMs show limited and domain-dependent performance on cognitive aptitude tasks relevant to medical school admission. High accuracy on knowledge-based examinations does not translate into stable performance on aptitude tests emphasizing fluid intelligence. The observed modality-dependent performance patterns and inter-run variability highlight the importance of differentiated, multi-run evaluation strategies when assessing LLMs for applications in medical education. Full article

Background/Objectives: Traditional histopathological classification of endometrial cancer (EC) exhibits limited prognostic precision due to interobserver variability and incomplete reflection of tumor biology. The Cancer Genome Atlas (TCGA) introduced molecular subtypes, with POLE-ultramutated tumors showing superior outcomes. This systematic review and meta-analysis assesses the prognostic impact of pathogenic/likely pathogenic POLE exonuclease-domain mutations (EDM) on survival in EC. Methods: PRISMA 2020-compliant search of PubMed, Embase, and Web of Science (2015–2025) identified 20 studies (n = 7708 EC patients; 159 POLE-mutant, 2.1%). Eligibility: Adult EC patients with POLE EDM vs. non-POLE, reporting OS/PFS/DFS/RFS/CSS hazard ratios (HR). ROBINS-I assessed bias; random-effects meta-analysis pooled multivariable HR. Results: The meta-analysis revealed a significantly reduced risk of death in POLE-mutant endometrial cancer patients, with an OS pooled hazard ratio (HR) of 0.35 (95% CI 0.21–0.58; I² = 17.9%) across eight studies. Disease control endpoints (DFS/PFS/RFS) from 10 studies showed an even more substantial benefit, with a pooled HR of 0.22 (95% CI 0.12–0.41; I² = 0%). Cancer-specific survival HRs ranged from 0.00 to 0.32 across four studies, often with zero events in POLE cohorts. ROBINS-I bias was low to moderate; heterogeneity stemmed from the comparators and stages. Conclusions: POLE-EDM confers a robust, favorable prognosis across EC stages, supporting molecular risk stratification and treatment de-escalation. Full article

Background: Gastric biopsy remains central to diagnosing Helicobacter pylori infection, autoimmune gastritis, intestinal metaplasia, dysplasia, and gastric cancer. However, morphology-based assessment is limited by interobserver variability, sampling constraints, and an incomplete ability to capture molecular heterogeneity and predict progression. Objective: This mini review summarizes how multi-omics technologies and artificial intelligence (AI) are modernizing gastric biopsy diagnostics, enabling precision classification, risk stratification, and workflow improvement. Methods: A narrative synthesis was undertaken across key literature on gastric pathology, multi-omics (genomics, transcriptomics, epigenomics, proteomics, lipidomics, metabolomics, microbiomics, and spatial approaches), and AI in endoscopy and computational pathology. Results: Multi-omics profiling enhances mechanistic understanding and refines disease classification by capturing clonal evolution, pathway dysregulation, immune–microenvironment interactions, and metabolic remodeling, with potential for biomarker discovery and therapy prediction. AI applications demonstrate strong performance across the gastric diagnostic pathway, including improved lesion detection during endoscopy, reduced miss rates, lesion segmentation, classification of precancerous conditions, H. pylori recognition, and near-expert histopathology classification. Evidence from systematic reviews supports robust diagnostic accuracy, while prospective studies highlight real-time feasibility. Conclusions: Integrating AI with multi-omics is shifting gastric biopsy from descriptive histology toward data-driven precision gastroenterology. Key barriers include dataset quality, standardization, interpretability, cost, and regulatory and ethical governance; addressing these will be essential for routine clinical adoption. Full article

This study deals with the evaluation of inter-observer reliability (IOR) among three raters in the case of dichotomous and trichotomous individual animal-based welfare indicators. The performance of the most documented agreement indices proposed in the literature was compared, using udder asymmetry (UA) as a dichotomous indicator and body condition score (BCS) as a trichotomous indicator, both obtained from the AWIN Goat protocol. Nine dairy goat farms, exploiting three alpine pastures (AP1 to AP3), were used for data collection. Krippendorff’s α, the agreement indices belonging to the Kappa statistic and their weighted forms were in some cases affected by the paradox behaviour. This phenomenon was observed for both UA and BCS [e.g., P_0(BCS-AP2) = 80%; Fleiss’ K = 0.22]. In the case of UA, Gwet’s γ(AC₁), followed by BP coefficient and Quatto’s S, gave the best agreement results [e.g., P_0(UA-AP1) = 86%; γ(AC₁) = 0.84]. In the case of BCS, the best agreement results were obtained with Gwet’s γ(AC₂), followed by the weighted forms of BP and S. When the evaluation is performed by three raters, γ(AC₁), BP and S are suggested to evaluate IOR in the case of both dichotomous and trichotomous indicators, while the related weighted forms are suitable for trichotomous indicators only. Full article

Background: The Balance Error Scoring System (BESS) is the most practiced static postural balance assessment tool, which relies on visual observation, and has been adopted as the gold standard in the clinic and field. However, the BESS can lead to missed and inaccurate diagnoses—because of its low inter-rater reliability and limited sensitivity—by missing subtle balance deficits, particularly in the athletic population. Smartphone technology using motion sensors may act as an alternative option for providing quantitative feedback to healthcare clinicians when performing balance assessments. The primary aim of this study was to explore the discriminative validity of an alternative novel smartphone-based cloud system to measure balance remotely in soccer athletes with and without hip pain. Methods: This is an exploratory cross-sectional study. A total of 64 Australian soccer athletes (128 hips, 28% females) between 18 and 40 years completed single and tandem stance balance tests that were scored using the modified BESS test and quantified using the smartphone device attached to their lower back. An Exploratory Factor Analysis (EFA) and a Clustered Receiver Operating Characteristic (ROC) using an Area Under the Curve (AUC) were used to explore the discriminative validity between the smartphone sensor system and the modified BESS test. A Linear Mixed-Effects Analysis of Covariance (ANCOVA) was used to determine any statistical differences in static balance measures between individuals with and without hip-related pain. Results: EFA revealed that the first factor primarily captured variance related to smartphone measurements, while the second factor was associated with modified BESS test scores. The ROC and the AUC showed that the smartphone sway measurements in the anterior–posterior and mediolateral directions during single-leg stance had an acceptable to excellent level of accuracy in distinguishing between individuals with and without hip-related pain (AUC = 0.72–0.80). Linear Mixed-Effects ANCOVA analysis found that individuals with hip-related pain had significantly less single-leg balance variability and magnitude in the anteroposterior and mediolateral directions compared to individuals without hip-related pain (p < 0.05). Conclusion: Due to the ability of smartphone technology to discriminate between individuals with and without hip-related pain during single-leg static balance tasks, it is recommended to use the technology in addition to the modified BESS test to optimise a clinician-led assessment and to further guide clinical balance decision-making. While the study supports smartphone technology as a method to assess static balance, its use in measuring balance during dynamic movements needs further research. Full article

Background/Objectives: Hydrocephalus is a complex neurological disorder marked by abnormal cerebrospinal fluid dynamics and ventricular enlargement. Despite breakthroughs in neuroimaging, diagnosis and longitudinal the application of imaging markers for the diagnosis and longitudinal monitoring of hydrocephalus remains challenging in routine clinical practice. The present study examines the behavior and cross-modality agreement of commonly used linear ventricular measurements under routine imaging conditions, at a single Romanian tertiary-care center characterized by heterogeneous acquisition protocols and limited availability of advanced volumetric techniques. Methods: We conducted a single-center retrospective observational study of 68 adults with hydrocephalus. Linear ventricular metrics, including Evans index and third-ventricle width, were measured on all available CT and MRI scans. CT–MRI agreement was assessed using paired examinations within a 90-day window. Longitudinal changes were analyzed using first–last and pre–post VP shunt comparisons. Associations between baseline imaging features and VP shunt placement were evaluated using rule-based and odds ratio analyses. Results: CT and MRI measurements demonstrated strong agreement for both Evans index (r = 0.93) and third-ventricle width (r = 0.90), with minimal systematic bias. Longitudinal analyses demonstrated small-magnitude changes in ventricular size following intervention, with substantial inter-individual variability. VP utilization increased across Evans index strata, reaching 100% in patients with values ≥0.50. Transependymal cerebrospinal fluid exudation showed the strongest association with subsequent VP shunting. Imaging-based rules exhibited expected trade-offs between sensitivity and specificity. Conclusions: Standard linear ventricular parameters exhibited adequate cross-modality agreement and clinically important longitudinal behavior in this cohort. While insufficient as standalone predictors, these readily available imaging markers remain important tools when combined with a comprehensive clinical assessment. Full article

Background/Objectives: Exercise-induced fatigue is a fundamental component of running performance and training, yet it is also implicated in altered movement mechanics and increased injury risk. While numerous studies have examined fatigue-related biomechanical changes during running, findings remain fragmented across biomechanical domains and fatigue modalities. The purpose of this systematic review was to synthesize contemporary evidence on the effects of fatigue on lower-limb biomechanics during running and to interpret the potential injury relevance of these adaptations. Methods: A systematic literature search was conducted in PubMed, Scopus, and Web of Science for original empirical studies published between January 2010 and December 2025. Eligible studies involved human participants performing running or running-related tasks, applied an explicit fatigue protocol, and reported quantitative lower-limb biomechanical outcomes. Study selection followed PRISMA 2020 guidelines. Data extraction included participant characteristics, fatigue protocols, biomechanical measures, instrumentation, and key findings. Methodological quality was assessed using the Cochrane Risk of Bias 2 (RoB-2) tool. Due to substantial methodological heterogeneity, findings were synthesized narratively. Results: Twenty-four studies met the inclusion criteria. Across studies, fatigue consistently altered spatiotemporal parameters, joint kinematic and kinetic variables, spring-mass behavior, impact loading, coordination variability, neuromuscular output, and inter-limb symmetry. Common adaptations included increased ground contact time, reduced ankle joint power and stiffness, increased joint range of motion, elevated impact loading, and greater movement variability. These changes reflected reduced mechanical efficiency and a redistribution of mechanical load from distal to proximal joints, particularly toward the knee and hip. Similar fatigue-related biomechanical patterns were observed in both laboratory-based and real-world endurance running conditions. Conclusions: Exercise-induced fatigue produces systematic and injury-relevant alterations in lower-limb biomechanics during running. These adaptations may preserve short-term performance but create mechanical conditions associated with increased susceptibility to overuse and non-contact injuries. Integrating fatigue-aware biomechanical assessment, neuromuscular conditioning, and individualized load management strategies may help mitigate adverse fatigue-related adaptations. Full article

Velocity, pressure, and density fields computed in earlier three-dimensional direct numerical simulations of a statistically stationary, planar, one-dimensional, low-Mach-number hydrogen–air flame propagating in small-scale, moderately intense, spatially decaying turbulence are filtered out using top-hat filters of four different widths. Certain source/sink filtered terms in the transport equations for resolved and subfilter-scale kinetic energies are analyzed. These are (i) the rate of inertial transfer of kinetic energy between resolved and subfilter scales, (ii) baropycnal work, (iii) subfilter-scale velocity–pressure–gradient term, and (iv) subfilter-scale pressure–dilatation term. These filtered terms are averaged over transverse planes and time or conditioned to the filtered combustion progress variable. Results show that terms (i) and (ii) work to transfer kinetic energy from smaller to larger scales (backscatter) and from larger to smaller scales, respectively, with the baropycnal work dominating the former term. These trends are observed for mean and conditional terms. The mean velocity–pressure–gradient term is positive and works to increase subfilter-scale kinetic energy due to combustion-induced thermal expansion. The pressure–dilatation term changes its sign from negative to positive at the leading and trailing edges, respectively, of the turbulent flame brush. Under conditions of the present study, the magnitudes of the mean velocity–pressure–gradient and pressure–dilatation terms are smaller when compared to the baropycnal work. Probability Density Functions (PDFs) for the explored filtered terms exhibit long tails, are highly skewed, and are characterized by a large kurtosis, thus implying significant intermittency of inter-scale energy transfer and energy exchange between internal and kinetic energy in the flame. These PDFs indicate that the intermittency of the inter-scale energy transfer and energy exchange depends substantially on mechanisms and scales of energy injection. Full article

Wearable sensing technologies are increasingly used to assess neuromuscular function during daily-life activities. This study presents and evaluates a multisensor wearable system integrating a textile-based surface Electromyography (sEMG) sleeve and a pressure-sensing insole for monitoring Tibialis Anterior (TA) and Gastrocnemius Lateralis (GL) activation during gait. Eleven healthy adults performed overground walking trials while synchronised sEMG and plantar pressure signals were collected and processed using a dedicated algorithm for detecting activation intervals across gait cycles. All participants completed the walking protocol without discomfort, and the system provided stable recordings suitable for further analysis. The detected activation patterns showed one to four bursts per gait cycle, with consistent TA activity in terminal swing and GL activity in mid- to terminal stance. Additional short bursts were observed in early stance, pre-swing, and mid-stance depending on the pattern. The area under the sEMG envelope and the temporal features of each burst exhibited both inter- and intra-subject variability, consistent with known physiological modulation of gait-related muscle activity. The results demonstrate the feasibility of the proposed multisensor system for characterising muscle activation during walking. Its comfort, signal quality, and ease of integration encourage further applications in clinical gait assessment and remote monitoring. Future work will focus on system optimisation, simplified donning procedures, and validation in larger cohorts and populations with gait impairments. Full article

In phenomenological studies of multiparticle production, transverse-momentum spectra measured in experiments frequently display an approximately power-law falloff, for which the Tsallis-type functional form is commonly employed as an effective parametrization. Within this framework, the emergence of such spectra is interpreted as a manifestation of nonextensive statistical behavior. An analogous power-law structure, however, can be reproduced without explicitly postulating Tsallis statistics by assuming the presence of intrinsic fluctuations of the local temperature (T) in the hadronizing medium; in that case, the observed deviations from a purely exponential spectrum are encapsulated by the nonextensivity index (q). We show that temperature fluctuation mechanisms capable of generating Tsallis-like power-law distributions in multiparticle production necessarily induce nontrivial inter-particle correlations among the emitted hadrons. Building on this observation, we outline a strategy to discriminate fluctuations realized on an event-by-event basis from those arising predominantly through event-to-event variability. Such a separation may be particularly pertinent for the characterization of high-multiplicity (high-density) final states produced at the Large Hadron Collider. Full article

A clinically useful classification system requires precise definitions, reproducibility, and applicability across different levels of clinical experience. Distal radioulnar joint instability remains insufficiently represented in fracture based classifications, contributing to diagnostic uncertainty and variability in treatment strategies. This retrospective observational study assessed the interobserver and intraobserver reliability of a previously proposed classification system for distal radioulnar joint instability. Five orthopedic surgeons, including three board-certified specialists and two final year residents, independently evaluated forty five clinical cases comprising distal radius fractures, Galeazzi fractures, and Essex Lopresti injuries, using predefined clinical and radiological criteria. Interobserver agreement was analyzed using Fleiss Kappa statistics, while intraobserver reliability was evaluated after a two week interval using Cohen Kappa. Overall interobserver agreement was excellent, with a global Fleiss Kappa value of 0.87. Agreement was highest in Galeazzi fractures and lowest in Essex Lopresti injuries, reflecting increased diagnostic complexity in this subgroup. Specialists demonstrated higher agreement than residents. Intraobserver reproducibility was excellent, with identical classifications in 96 percent of reassessed cases. These findings indicate that the proposed classification system shows high reliability and reproducibility, supporting its potential clinical utility for standardized assessment of distal radioulnar joint instability and for guiding future clinical and biomechanical research. Full article