Bioengineering最新文献

{"title":"Timing-Dependent Neuromuscular Responses to Pulsed Electromagnetic Field (PEMF) Stimulation During Cycling Exercise in Sedentary Males.","authors":"Aurelio Trofè, Alessandro Piras, Michela Persiani, Luca Breviglieri, Alessandra Laffi, Andrea Meoni, Milena Raffi","doi":"10.3390/bioengineering13101165","DOIUrl":"https://doi.org/10.3390/bioengineering13101165","url":null,"abstract":"<p><p>Pulsed electromagnetic field (PEMF) increases the amplitude of muscle activity during physical exercise. This study investigated the effects of PEMF stimulation timing on neuromuscular activation in young sedentary males, during moderate-intensity constant-load cycling. We examined whether a PEMF applied at the beginning or during the middle of continuous exercise elicits differential effects on muscle activation. The participants performed a 30 min cycling task at 50% of VO₂max in which PEMF stimulation was alternately activated or deactivated in 15 min bouts. Surface electromyography (EMG) was recorded from the right vastus medialis and biceps femoris, and blood lactate samples were collected at baseline and during exercise. Data were analyzed via linear mixed-effects modeling. Active PEMF stimulation significantly increased normalized EMG amplitude in the vastus medialis (<i>p</i> < 0.001) and biceps femoris (<i>p</i> = 0.001) compared to inactive conditions, with the greatest effect observed when stimulation was applied after 15 min of exercise. Blood lactate concentrations were significantly elevated during PEMF application relative to baseline and inactive stimulation (<i>p</i> < 0.001). The timing of PEMF stimulation influenced neuromuscular responses during exercise, highlighting its potential as a tool to modulate muscle performance in sedentary individuals.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 10","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149261682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Imaging Approaches to Quantifying the Biomechanical Properties of the Human Vitreous In Vivo: A Review.","authors":"Taariq Mohammed, Giuliano Scarcelli, Osamah Saeedi","doi":"10.3390/bioengineering13101164","DOIUrl":"https://doi.org/10.3390/bioengineering13101164","url":null,"abstract":"<p><p>The biomechanics of the vitreous humor undergo important changes in both normal aging and various pathologic conditions. While these changes are clinically visible, there are limited objective in vivo measurements of vitreous biomechanics. New imaging modalities have the potential to enable quantitative assessment of vitreous properties such as viscoelasticity in vivo, which could have relevance in assessing the risk of progression of vitreoretinal diseases. In this article, we discuss the current clinical approaches to vitreous biomechanics and review relevant new imaging methods with potential for clinical translation.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 10","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149261613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spectral-Distribution Uncertainty Modeling for Robust Cross-Domain Medical Image Segmentation.","authors":"Chao Xin, Zhixiong Chen, Zeyu Huang, Jiucun Wang, Luojun Lin","doi":"10.3390/bioengineering13101163","DOIUrl":"https://doi.org/10.3390/bioengineering13101163","url":null,"abstract":"<p><p>Domain generalization (DG) for medical image segmentation is commonly approached by simulating domain shifts through deterministic image transformations or feature perturbations. However, such methods implicitly assume that unseen domains can be approximated by predefined appearance variations. In this work, we challenge this assumption and hypothesize that medical domain shifts are more fundamentally characterized as uncertainty in spectral distributions. While anatomical structures are largely preserved across institutions, scanners, and acquisition protocols, substantial variations arise in image appearance, texture, and artifacts, which are predominantly manifested in the spectral domain. To test this hypothesis, we propose Spectral-Distribution Uncertainty (SDU), a frequency-aware DG framework that explicitly models uncertainty in the Fourier amplitude distributions of intermediate representations. By decomposing Transformer features into amplitude and phase components, SDU disentangles domain-specific spectral characteristics from domain-invariant anatomical semantics. Instead of imposing handcrafted frequency perturbations, SDU estimates spectral-distribution uncertainty during training and injects stochastic variations into the amplitude space, synthesizing diverse yet anatomically consistent representations that emulate potential unseen domains. Consequently, SDU expands the support of spectral feature distributions, enabling the model to learn representations that are robust to uncertainty-induced spectral shifts. Extensive experiments on retinal fundus and prostate MRI benchmarks demonstrate that SDU consistently outperforms state-of-the-art DG methods. Beyond empirical gains, these findings provide evidence that medical domain shifts are more appropriately characterized as uncertainty in spectral feature distributions, offering a principled perspective for generalizable medical image segmentation.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 10","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149261686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine Learning Applied to Montreal Cognitive Assessment Subdomains for Differential Diagnosis of Neurodegenerative Movement Disorders: Classification Limits and Deterministic Score Reconstruction.","authors":"Kazeem B Olanrewaju, Ngozi D Mbue","doi":"10.3390/bioengineering13101161","DOIUrl":"https://doi.org/10.3390/bioengineering13101161","url":null,"abstract":"<p><p>Early differentiation of neurodegenerative movement disorders remains challenging because of overlapping cognitive-behavioral profiles. The Montreal Cognitive Assessment (MoCA) is a widely used 30-point screening instrument; however, the extent to which MoCA subdomain scores alone can support automated multi-class differential diagnosis or score prediction requires rigorous methodological evaluation. In this study, we investigated supervised machine learning algorithms across two distinct tasks using clinical data from the National Institute of Neurological Disorders and Stroke (NINDS) Parkinson's Disease Biomarkers Program (N=64): (1) multi-class classification across movement disorder diagnoses, including Parkinson's disease (PD, n=27), No Neurological Diagnosis (Controls, n=14), Progressive Supranuclear Palsy (PSP, n=9), Essential Tremor (ET, n=8), Corticobasal Degeneration (CBD, n=1), Multiple System Atrophy (MSA, n=1), and Other (n=4); and (2) numerical prediction/reconstruction of the MoCA total score from its constitutive domain items, with external validation on 1499 records from the Parkinson's Progression Markers Initiative (PPMI). Under stratified 5-fold cross-validation, multi-class diagnostic classification was severely limited: the highest macro-averaged F1-score achieved by any trained model was 0.362 (95% CI: 0.284-0.440; Logistic Regression), trailing a naive Constant majority-class baseline in classification accuracy (0.463 vs. 0.366). Bootstrap resampling yielded apparent increases in performance (Neural Network macro-F1: 0.558, 95% CI: 0.512-0.604; AdaBoost: 0.555); however, this reflects optimistic bias from pseudo-replicate sampling rather than genuine clinical generalizability. For continuous score modeling, Linear Regression and Stochastic Gradient Descent achieved near-perfect internal fit (R2=1.000 and 0.996, respectively), and retained near-perfect performance in the external PPMI cohort (R2=0.992 and 0.991; MSE ≤0.077). We demonstrate that this regression success reflects the mathematical recovery of an additive scoring definition, i.e., target leakage, rather than independent clinical prediction. MoCA domain scores alone possess insufficient disease-specific variance to differentiate complex parkinsonian syndromes, underscoring that automated clinical classification requires the integration of multimodal neuroimaging, fluid, and digital motor biomarkers.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 10","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149261721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Influence of Implant Macrogeometry on Primary Stability in Different Polyurethane Bone-Density Models: An In Vitro Study.","authors":"Margherita Tumedei, Ugo Graziani, Alessandro Cipollina, Renato Ori, Adriano Piattelli, Ugo Covani, Lorenzo Enia, Calogero Pitruzzella, Francesca Mangione","doi":"10.3390/bioengineering13101162","DOIUrl":"https://doi.org/10.3390/bioengineering13101162","url":null,"abstract":"<p><strong>Background: </strong>Primary stability (PS) is a crucial determinant of long-term dental implant success, particularly in compromised or low-density bone sites. While macrogeometry is known to influence initial mechanical anchorage, the specific contribution of thread dimensions across varying bone densities remains incompletely understood. This in vitro study evaluated the influence of two different implant macrogeometries characterized by distinct thread configurations on primary implant stability within standardized polyurethane foam models representing different bone qualities.</p><p><strong>Methods: </strong>Two implant designs featuring distinct thread profiles were tested: the Evolution KRI (larger threads, pitch 1.8-2.2 mm, depth 0.55-1.025 mm) and the Evolution PRI (smaller threads, pitch 1.0 mm, depth 0.5 mm), across three fixture diameters (4.0, 4.5, and 5.0 mm). Implants were inserted into three standardized polyurethane block configurations: Group I (25 PCF uniform block, simulating D2 dense trabecular bone), Group II (10 PCF trabecular base with a 3 mm 40 PCF cortical layer, simulating D3 bone), and Group III (12.5 PCF trabecular base with a 2 mm 40 PCF cortical layer, simulating D4 bone). Each experimental group included 10 implants (n = 10). Two RFA measurements were collected for each implant and averaged prior to statistical analysis. Group comparisons were performed using one-way ANOVA followed by Tukey's post hoc test. Primary stability was quantitatively assessed using Resonance Frequency Analysis (RFA) to record Implant Stability Quotient (ISQ) scores.</p><p><strong>Results: </strong>Statistically significant differences in ISQ values were observed among the experimental groups (F=9.909,p<0.0001,R2=0.4785). Implants featuring larger threads (KRI) demonstrated consistently higher mean ISQ scores compared to smaller-thread implants (PRI) across all bone densities. In Group I (D2 model), KRI implants achieved a significantly higher mean ISQ than PRI implants (67.1 ± 1.91 vs. 65.1 ± 1.43; <i>p</i> = 0.0472). In Group II (D3 model with 3 mm cortical layer), this difference was most pronounced, with KRI reaching 68.5±0.58 compared to 64.8 ± 2.15 for PRI (<i>p</i> < 0.0001). In Group III (D4 model with 2 mm cortical layer), KRI maintained a higher stability trend (68.0±0.93 vs. 66.5±1.42), though the inter-system difference did not reach statistical significance (p=0.2401). Inter-group comparisons confirmed that the highest overall primary stability was obtained by large-thread implants in the presence of a 3 mm cortical layer.</p><p><strong>Conclusions: </strong>Thread macrogeometry significantly influences primary implant stability; the tested KRI macrogeometry demonstrated higher ISQ values than the PRI macrogeometry under specific polyurethane configurations, particularly in intermediate trabecular-cortical bone structures.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 10","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149261635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biomaterial-Based Regulation of Mesenchymal Stromal Cell Hepatic Differentiation for Liver Regeneration.","authors":"Lexi Balster, Ramy A Hinna, Ayman A Hassan, Gamal Shiha, Ahmed Lotfy","doi":"10.3390/bioengineering13101157","DOIUrl":"https://doi.org/10.3390/bioengineering13101157","url":null,"abstract":"<p><p>Liver failure and advanced chronic liver disease remain major causes of morbidity and mortality, while donor organ shortages, procedural complexity, cost, and the need for lifelong management after transplantation limit the availability of liver transplantation. Mesenchymal stromal cells (MSCs) have attracted substantial interest as a cell source for liver regeneration because of their accessibility, expansion capacity, immunomodulatory properties, and regenerative secretome. MSC-based hepatic differentiation, however, remains challenging, and cells generated in vitro frequently display an incomplete hepatocyte phenotype and limited maturation. Increasing evidence indicates that soluble differentiation factors alone are insufficient to reproduce the complex microenvironmental cues that regulate hepatic cell fate. Biomaterials can provide three-dimensional architecture, extracellular matrix (ECM) ligands, mechanical cues, cell-adhesive sites, and controlled presentation of growth factors, thereby acting as more than passive carriers of cells. In this mini-review, we summarize studies investigating natural and synthetic biomaterials for MSC hepatic differentiation, with emphasis on collagen-, gelatin-, heparin-, alginate-, and decellularized ECM-based systems as well as synthetic polymeric scaffolds such as poly(lactic-co-glycolic acid) and poly(L-lactic acid)-co-poly(ε-caprolactone). We discuss how biomaterial composition and three-dimensional organization may cooperate with hepatic differentiation media to promote hepatic phenotype and function. We also highlight an important distinction between expression of hepatic markers and acquisition of mature hepatocyte function, and identify opportunities for biomaterial systems that integrate biochemical, biophysical, and paracrine cues to achieve more reproducible hepatic maturation and clinically relevant liver regeneration.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 10","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149261644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Periodicity-Driven Adaptive Localization of Respiratory Regions for Non-Contact Respiration Monitoring in Sleeping Infants.","authors":"Hyoyeong Jeong, Jinsoo Kim, Eui Chul Lee","doi":"10.3390/bioengineering13101158","DOIUrl":"https://doi.org/10.3390/bioengineering13101158","url":null,"abstract":"<p><p>Respiration is a critical vital sign for assessing the health status of infants during the first year of life. Conventional video-based respiratory monitoring methods often rely on manually defined regions of interest (ROIs) targeting specific anatomical regions, such as the chest or abdomen, or employ pretrained object detection models to localize body regions before extracting respiratory signals. However, in unconstrained sleep environments, infants may adopt diverse sleep postures, making it difficult to assume that respiration-induced movements will consistently appear in the same anatomical region or image location. To address this limitation, we propose an anchor-based respiratory-region localization framework that identifies spatial regions exhibiting prominent respiratory periodicity across the entire video frame without relying on predefined anatomical ROIs or separate body-region localization models. For each grid cell, time-series signals are constructed from inter-frame color/intensity variations and optical-flow-derived motion changes. The magnitude spectra of these signals are then multiplied element-wise to generate a respiratory periodicity map representing the spatial distribution of respiration-related periodicity across the frame. The grid cell with the highest Periodicity Score is selected as the Anchor Grid Cell and used as the primary respiratory region for respiratory-rate estimation. The proposed method was evaluated using 6-fold subject-wise cross-validation on 374 video clips from 15 infants. The single-Anchor Grid Cell approach achieved a mean absolute error (MAE) of 1.9953 breaths per minute (BPM), a root mean square error (RMSE) of 3.9681 BPM, and a Pearson correlation coefficient (PCC) of 0.7287. Moreover, MAEs below 2.5 BPM were obtained for the supine, side-lying, and prone postures, indicating consistent estimation performance across the evaluated sleep postures. These findings suggest that respiration-related information in infants is not necessarily confined to predefined anatomical regions and may instead be expressed at different spatial locations depending on sleep posture.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 10","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149261566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pulsed Electromagnetic Fields and Bioimpedance Monitoring of Peripheral Circulation: A Scoping Review and Proposed Adaptive Control Framework.","authors":"Ahmad Hammoud, Andrey Briko, Vladislava Kapravchuk, Artem Malakhov, Sergey Shchukin","doi":"10.3390/bioengineering13101160","DOIUrl":"https://doi.org/10.3390/bioengineering13101160","url":null,"abstract":"<p><p>Evidence for pulsed electromagnetic fields (PEMFs) in peripheral circulatory dysfunction is heterogeneous, while limb bioimpedance may index segmental pulsatile hemodynamics. This scoping review mapped PEMF effects, bioimpedance-based vascular assessment, and adaptive stimulation architectures. Scopus, PubMed, and Web of Science were searched in July 2026, supplemented by IEEE Xplore during revision (PRISMA-ScR reporting; no registered protocol). The main search used AI-assisted sequential investigator review; IEEE records underwent independent duplicate human screening. The main search yielded 1750 unique records and 30 core reports; IEEE Xplore added two technical reports. The combined corpus comprised 32 reports, conservatively grouped into 30 study/report clusters. It contained 15 direct clinical, six clinical support/proxy, five preclinical/veterinary, and six technical/pilot reports; 26 were assessed in full text and six from abstracts. Reported outcomes included positive, mixed, and negative directions; heterogeneous endpoints and designs, and the absence of formal risk-of-bias assessment precluded efficacy inference. Low-frequency, low-millitesla regimens recurred, but incomplete and non-equivalent dose reporting precluded identification of an optimal regimen. Contextual bioimpedance evidence supported segmental impedance and pulse-related hemodynamic assessment, not direct measurement of capillary microcirculation. No validated system adapting PEMF from limb bioimpedance for a peripheral-circulation target was identified in the databases searched. The proposed adaptive architecture requires prospective technical and clinical validation.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 10","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149261620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Designing Protective Systems and Selecting Materials for Motorsport Safety Through Biomechanical Evidence: A Scoping Review.","authors":"Jiongxiang Zhao, Enze Shao, Zilong Lu, Jun Wen, Chao Zeng, Tibor J Goda, Viktória Tafferner-Gulyás, Dong Sun, Yaodong Gu","doi":"10.3390/bioengineering13101159","DOIUrl":"https://doi.org/10.3390/bioengineering13101159","url":null,"abstract":"<p><p>Motorsport remains high risk despite advances in crash protection, vehicle design, and medical response. Effective injury prevention requires understanding interactions among crash loading, human injury tolerance, protective-system design, and material behavior. This scoping review searched PubMed, Web of Science, IEEE Xplore, and Scopus for English-language studies from 2000 to July 2026 addressing motorsport safety, injury biomechanics, finite element analysis or modeling, protective-system design, or impact-mitigation materials. Study characteristics were charted, and evidence was narratively synthesized following scoping-review principles. Fifty-six studies were included. Injury prevention increasingly draws on head-kinematic field measurements, injury epidemiology, region-specific finite element analyses, and studies of helmets, restraints, seats, and energy-absorbing structures. The most direct evidence concerns integrated head-neck protection, restraint and seat geometry, and the use of finite-element methods to interpret local injury mechanisms. Emerging material strategies are promising but rely mainly on component-level or simulation-based evidence rather than driver-level injury outcomes. Overall, biomechanics, protective-system design, and material selection are increasingly integrated, but evidence remains uneven. Real-world injury surveillance is limited, simulation studies predominate over field outcomes, and direct evidence linking emerging materials to driver-level injury reduction remains sparse. Progress requires better surveillance datasets, stronger motorsport-specific validation, and more driver-centered protective design.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 10","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149261575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Use of Artificial Intelligence for Estimating Trabecular-Iris Angle from Slit-Lamp Images Developed Using Anterior-Segment Optical Coherence Tomography.","authors":"Takahiro Mizukami, Jun Ohashi, Hiroki Nishimura, Ryota Yokoiwa, Yuji Takayanagi, Hirotsugu Soga, Shintato Nakayama, Eisuke Shimizu","doi":"10.3390/bioengineering13101156","DOIUrl":"https://doi.org/10.3390/bioengineering13101156","url":null,"abstract":"<p><p><b>Background:</b> Narrowing of the trabecular-iris angle (TIA) is a key anatomical feature of primary angle-closure disease and contributes to impaired aqueous humor outflow; however, conventional angle assessment requires specialized expertise or costly imaging equipment. This study aimed to develop an artificial intelligence model for quantitative TIA estimation from anterior-segment images acquired with a smartphone-attached slit-lamp microscope. <b>Methods:</b> In this retrospective study, 127,512 candidate frames were extracted from anterior-segment videos obtained from 2654 eyes. After automated diagnosability filtering, 59,412 frames suitable for TIA500 estimation were retained and assigned to the training, validation, and test datasets using patient-level grouping. A ResNet50-based model was trained to estimate inferior, nasal, and temporal TIA500 values using the corresponding measurements obtained by anterior-segment optical coherence tomography (AS-OCT) as the ground-truth reference. Model performance was evaluated by comparing the AI-predicted values with the AS-OCT measurements using mean absolute error (MAE), root mean squared error (RMSE), Spearman's rank correlation coefficient, and the intraclass correlation coefficient (ICC). <b>Results:</b> Per-eye MAEs were 7.01° ± 5.69°, 7.28° ± 5.80°, and 7.90° ± 6.37° for inferior, nasal, and temporal TIA, respectively. Corresponding correlations with reference measurements were 0.683, 0.696, and 0.646, while ICCs were 0.769, 0.764, and 0.743 (all <i>p</i> < 0.001). <b>Conclusions:</b> These findings demonstrate the feasibility of estimating TIA500 from smartphone-based slit-lamp images. However, the moderate correlations with AS-OCT measurements indicate that the present model is not yet sufficiently accurate for independent clinical diagnosis or screening, and further model improvement and external validation are required.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"13 10","pages":""},"PeriodicalIF":4.4,"publicationDate":"2026-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149261684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}