BioMedical Engineering OnLine最新文献

{"title":"WDRIV-Net: a weighted ensemble transfer learning to improve automatic type stratification of lumbar intervertebral disc bulge, prolapse, and herniation.","authors":"Ichiro Nakamoto, Hua Chen, Rui Wang, Yan Guo, Wei Chen, Jie Feng, Jianfeng Wu","doi":"10.1186/s12938-025-01341-4","DOIUrl":"10.1186/s12938-025-01341-4","url":null,"abstract":"<p><p>The degeneration of the intervertebral discs in the lumbar spine is the common cause of neurological and physical dysfunctions and chronic disability of patients, which can be stratified into single-(e.g., disc herniation, prolapse, or bulge) and comorbidity-type degeneration (e.g., simultaneous presence of two or more conditions), respectively. A sample of lumbar magnetic resonance imaging (MRI) images from multiple clinical hospitals in China was collected and used in the proposal assessment. We devised a weighted transfer learning framework WDRIV-Net by ensembling four pre-trained models including Densenet169, ResNet101, InceptionV3, and VGG19. The proposed approach was applied to the clinical data and achieved 96.25% accuracy, surpassing the benchmark ResNet101 (87.5%), DenseNet169 (82.5%), VGG19 (88.75%), InceptionV3 (93.75%), and other state-of-the-art (SOTA) ensemble deep learning models. Furthermore, improved performance was observed as well for the metric of the area under the curve (AUC), producing a ≥ 7% increase versus other SOTA ensemble learning, a ≥ 6% increase versus most-studied models, and a ≥ 2% increase versus the baselines. WDRIV-Net can serve as a guide in the initial and efficient type screening of complex degeneration of lumbar intervertebral discs (LID) and assist in the early-stage selection of clinically differentiated treatment options.</p>","PeriodicalId":8927,"journal":{"name":"BioMedical Engineering OnLine","volume":"24 1","pages":"11"},"PeriodicalIF":2.9,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11800529/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143363551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Relationship between RSV-hospitalized children and meteorological factors: a time series analysis from 2017 to 2023.","authors":"Shuying Wang, Yifan Wang, Yingxue Zou, Cheng-Liang Yin","doi":"10.1186/s12938-025-01339-y","DOIUrl":"10.1186/s12938-025-01339-y","url":null,"abstract":"<p><strong>Objectives: </strong>Respiratory syncytial virus (RSV) is a leading cause of hospitalization for lower respiratory tract infections amongst infants under 1 year, posing a significant global health challenge. The incidence of RSV exhibits marked seasonality and is influenced by various meteorological factors, which vary across regions and climates. This study aimed to analyze seasonal trends in RSV-related hospitalization in Tianjin, a region with a semi-arid and semi-humid monsoon climate, and to explore the relationship between these trends and meteorological factors. This research intends to inform RSV prevention strategies, optimize public health policies and medical resource allocation while also promoting vaccine and therapeutic drug development.</p><p><strong>Methods: </strong>This study analyzed data from a cohort of 6222 children hospitalized with RSV-related infections. Meteorological data were collected from the Tianjin Binhai International Airport meteorological station, encompassing temperature (℃), air pressure (mmHg), wind speed (m/s), humidity (%), and precipitation (mm). We employed seasonal ARIMA and GAM models to investigate the association between meteorological factors and RSV-related hospitalizations.</p><p><strong>Results: </strong>The SARIMA (1,0,0) (0,1,2)12 model effectively predicted RSV-related hospital admissions. Spearman correlation and GAM analysis revealed a significant negative association between the monthly average temperature and RSV hospitalizations.</p><p><strong>Conclusions: </strong>Our findings indicated that meteorological factors influence RSV infection-related hospital admissions, with higher monthly average temperatures associated with fewer hospitalizations. The predictive capabilities of the SARIMA model bolster the formulation of targeted RSV prevention strategies, enhancing public health policy and medical resource allocation. Furthermore, continued research into vaccines and therapeutic drugs remains indispensable for augmenting public health outcomes.</p>","PeriodicalId":8927,"journal":{"name":"BioMedical Engineering OnLine","volume":"24 1","pages":"10"},"PeriodicalIF":2.9,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11796253/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143254256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated orthodontic diagnosis via self-supervised learning and multi-attribute classification using lateral cephalograms.","authors":"Qiao Chang, Yuxing Bai, Shaofeng Wang, Fan Wang, Shuang Liang, Xianju Xie","doi":"10.1186/s12938-025-01345-0","DOIUrl":"10.1186/s12938-025-01345-0","url":null,"abstract":"<p><strong>Background: </strong>Malocclusion, characterized by dental misalignment and improper occlusal relationships, significantly impacts oral health and daily functioning, with a global prevalence of 56%. Lateral cephalogram is a crucial diagnostic tool in orthodontic treatment, providing insights into various structural characteristics.</p><p><strong>Methods: </strong>This study introduces a pre-training approach using multi-center lateral cephalograms for self-supervised learning, aimed at improving model generalization across diverse clinical data domains. Additionally, a multi-attribute classification network is proposed, leveraging attribute correlations to optimize parameters and enhance classification performance.</p><p><strong>Results: </strong>Comprehensive evaluation on both public and clinical datasets showcases the superiority of the proposed framework, achieving an impressive average accuracy of 90.02%. The developed Self-supervised Pre-training and Multi-Attribute (SPMA) network achieves a best match ratio (MR) score of 71.38% and a low Hamming loss (HL) of 0.0425%, demonstrating its efficacy in orthodontic diagnosis from lateral cephalograms.</p><p><strong>Conclusions: </strong>This work contributes significantly to advancing automated diagnostic tools in orthodontics, addressing the critical need for accurate and efficient malocclusion diagnosis. The outcomes not only improve the efficiency and accuracy of diagnosis, but also have the potential to reduce healthcare costs associated with orthodontic treatments.</p>","PeriodicalId":8927,"journal":{"name":"BioMedical Engineering OnLine","volume":"24 1","pages":"9"},"PeriodicalIF":2.9,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11792313/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143188028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A model-based spectral directional approach reveals the long-term impact of COVID-19 on cardiorespiratory control and baroreflex.","authors":"Beatrice Cairo, Francesca Gelpi, Vlasta Bari, Martina Anguissola, Pavandeep Singh, Beatrice De Maria, Marco Ranucci, Alberto Porta","doi":"10.1186/s12938-024-01327-8","DOIUrl":"10.1186/s12938-024-01327-8","url":null,"abstract":"<p><strong>Background: </strong>Coronavirus disease 19 (COVID-19) patients might develop sequelae after apparent resolution of the infection. Autonomic dysfunction and baroreflex failure have been frequently reported. However, the long-term effect of COVID-19 on cardiorespiratory and cardiovascular neural controls has not been investigated with directional approaches able to open the closed-loop relationship between physiological variables.</p><p><strong>Methods: </strong>A model-based causal spectral approach, namely causal squared coherence (CK²), was applied to the beat-to-beat variability series of heart period (HP) and systolic arterial pressure (SAP), and to the respiratory signal (RESP) acquired at rest in supine position and during active standing (STAND) in COVID-19 survivors 9 months after their hospital discharge. Patients were categorized according to their need of ventilatory support during hospitalization as individuals that had no need of continuous positive airway pressure (noCPAP, n = 27), need of continuous positive airway pressure in sub-intensive care unit (CPAP, n = 14) and need of invasive mechanical ventilation in intensive care unit (IMV, n = 8).</p><p><strong>Results: </strong>The expected decrease of the strength of the HP-RESP dynamic interactions as well as the expected increase of the dependence of HP on SAP along baroreflex during STAND was not observed and this result held regardless of the severity of the disease, namely in noCPAP, CPAP and IMV cohorts. Regardless of the experimental condition, spectral causality markers did not vary across groups either.</p><p><strong>Conclusions: </strong>CK² markers, in association with an orthostatic challenge, were able to characterize the impairment of cardiorespiratory control and baroreflex in COVID-19 patients long after acute infection resolution and could be exploited to monitor the evolution of the COVID-19 patients after hospital discharge.</p>","PeriodicalId":8927,"journal":{"name":"BioMedical Engineering OnLine","volume":"24 1","pages":"8"},"PeriodicalIF":2.9,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11792257/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143121986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning-based algorithm for classifying high-resolution computed tomography features in coal workers' pneumoconiosis.","authors":"Hantian Dong, Biaokai Zhu, Xiaomei Kong, Xuesen Su, Ting Liu, Xinri Zhang","doi":"10.1186/s12938-025-01333-4","DOIUrl":"10.1186/s12938-025-01333-4","url":null,"abstract":"<p><strong>Background: </strong>Coal workers' pneumoconiosis is a chronic occupational lung disease with considerable pulmonary complications, including irreversible lung diseases that are too complex to accurately identify via chest X-rays. The classification of clinical imaging features from high-resolution computed tomography might become a powerful clinical tool for diagnosing pneumoconiosis in the future.</p><p><strong>Methods: </strong>All chest high-resolution computed tomography (HRCT) medical images presented in this work were obtained from 217 coal workers' pneumoconiosis (CWP) patients and dust-exposed workers. We segmented regions of interest according to the diagnostic results, which were evaluated by radiologists. These regions were then classified regions into four categories. We employed an efficient deep learning model and various image augmentation techniques (DenseNet-ECA). The classification performance of the different deep learning models was assessed, and receiver operating characteristic (ROC) curves and accuracy (ACC) were used to determine the optimal algorithm for classifying CWP clinical imaging features obtained from HRCT images.</p><p><strong>Results: </strong>Four primary clinical imaging features in HRCT images, with a total of more than 1700 regions of interest (ROIs), were annotated, augmented, and used as a training set for tenfold cross-validation to generate the model. We selected DenseNet-Attention Net as the optimal model through assessing the performance of different classification algorithms, which yielded an average area under the ROC curve (AUC) of 0.98, and all clinical imaging features were classified with an AUC greater than 0.92. For the individual classifications, the AUCs were as follows: small miliary opacities, 0.99; nodular opacities, 1.0; interstitial changes, 0.92; and emphysema, 1.0.</p><p><strong>Conclusion: </strong>We successfully applied a data augmentation strategy to develop a deep learning model by combining DenseNet with ECA-Net. We used our novel model to automatically classify CWP clinical imaging features from 2D HRCT images. This successful application of a deep learning-data augmentation algorithm can help clinical radiologists by providing reliable diagnostic information for classification.</p><p><strong>Trial registration: </strong>Chinese Clinical Trial Registry, ChiCTR2100050379. Registered on 27 August 2021, https://www.chictr.org.cn/bin/project/edit?pid=132619 .</p>","PeriodicalId":8927,"journal":{"name":"BioMedical Engineering OnLine","volume":"24 1","pages":"7"},"PeriodicalIF":2.9,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11773871/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143051432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research progress in the regulation of endothelial cells and smooth muscle cells using a micro-nanostructure.","authors":"Songhao Liu, Juan Yan, Mengyu Gao, Hongxia Yang","doi":"10.1186/s12938-025-01337-0","DOIUrl":"10.1186/s12938-025-01337-0","url":null,"abstract":"<p><p>Recently, the incidence rate and mortality of various acute or chronic vascular occlusive diseases have increased yearly. As one of the most effective measures to treat them, vascular stents have been widely studied by researchers, and presently, the most commonly used is a drug-eluting stent, which reduces the process of rapid endothelialization because the drug is not selective. Fortunately, with the discovery and exploration of micro-nanostructures that can regulate cells selectively, reducing the incidence of \"intravascular restenosis\" and achieving rapid endothelialization simultaneously are possible through a special structure that cannot only improve endothelial cells (ECs), but also inhibit smooth muscle cells (SMCs). Therefore, this paper mainly introduces the preparation methods of micro-nanostructures used in the past, as well as the detection methods of EC and SMC. Then, the various functions of different dimensional structures for different cells are summarized and analyzed. Finally, the application of micro-nanostructure in future stent materials is summarized and proposed.</p>","PeriodicalId":8927,"journal":{"name":"BioMedical Engineering OnLine","volume":"24 1","pages":"6"},"PeriodicalIF":2.9,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11760742/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143027797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"4D printing: innovative solutions and technological advances in orthopedic repair and reconstruction, personalized treatment and drug delivery.","authors":"Chenxi Shen, Aiyong Shen","doi":"10.1186/s12938-025-01334-3","DOIUrl":"10.1186/s12938-025-01334-3","url":null,"abstract":"<p><p>With precise control of smart materials deformation in time dimension, doctors can customize orthopedic implants. This review focuses on the advances of 4D printing technology in orthopedics, including its applications in bone repair and reconstruction, personalized treatment, and drug delivery. 4D printing enables the creation of bionic scaffolds and fixation devices for bone repair, customized implants matching patients' conditions for personalized treatment, and specific carriers for accurate drug release and delivery, which together contribute to accelerating bone healing, providing exclusive treatments, enhancing therapeutic effects and reducing side effects, thus helping improve orthopedic medicine. It offers comprehensive reference materials for relevant medical personnel.</p>","PeriodicalId":8927,"journal":{"name":"BioMedical Engineering OnLine","volume":"24 1","pages":"5"},"PeriodicalIF":2.9,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11748259/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142999525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Portable devices for periodic monitoring of bioelectrical impedance along meridian pathways in healthy individuals.","authors":"Yu-Chen Xu, Xiu-Yan Cao, Shuai Liu, Bo Liu, Hao Chen, Min Cheng, Wei-Hua Ye","doi":"10.1186/s12938-025-01335-2","DOIUrl":"10.1186/s12938-025-01335-2","url":null,"abstract":"<p><strong>Objective: </strong>This study aims to investigate the monthly variation patterns of bioelectrical impedance (BEI) along 24 meridian pathways in healthy individuals.</p><p><strong>Methods: </strong>A cohort of 684 healthy middle-aged participants from North China was enrolled between July 1, 2017, and September 5, 2020. BEI measurements were consistently recorded along the 24 meridian pathways over the study period. The collected BEI data were subjected to statistical analysis, and line charts were constructed to depict the temporal variation patterns.</p><p><strong>Results: </strong>Analysis revealed that BEI values along the 24 meridian pathways followed a normal distribution over a 12-month period. In the first group of meridians, which includes the lung, large intestine, heart, small intestine, pericardium, and triple-energizer meridians, significant monthly variations were observed. The second group, comprising the spleen, stomach, bladder, kidney, gallbladder, and liver meridians, exhibited marked differences primarily between March and April (P < 0.05), with a peak in April and relatively stable values thereafter. Synchronous BEI fluctuations were evident on the left and right sides of the body, and both groups of meridian pathways displayed similar variation patterns. These patterns largely corresponded to fluctuations observed in the spleen meridian.</p><p><strong>Conclusion: </strong>The consistent monthly variation patterns in BEI along the 24 meridian pathways among healthy middle-aged individuals align with Traditional Chinese Medicine (TCM) concepts of meridians and collaterals. The spleen meridian, in particular, appears to play a crucial role in influencing these bioelectrical fluctuations, as posited in TCM theory. From a bioelectrical standpoint, this study provides empirical support for the potential existence and functionality of meridians and collaterals, offering a scientific perspective that complements ancient TCM principles.</p>","PeriodicalId":8927,"journal":{"name":"BioMedical Engineering OnLine","volume":"24 1","pages":"3"},"PeriodicalIF":2.9,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11740341/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142999530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The potential of MRI radiomics based on extrapulmonary metastases in predicting EGFR mutations: a systematic review and meta-analysis.","authors":"Linyong Wu, Dayou Wei, Songhua Li, Shaofeng Wu, Yan Lin, Lifei Chen","doi":"10.1186/s12938-025-01331-6","DOIUrl":"10.1186/s12938-025-01331-6","url":null,"abstract":"<p><strong>Background: </strong>Epidermal growth factor receptor (EGFR) gene mutations can lead to distant metastasis in non-small cell lung cancer (NSCLC). When the primary NSCLC lesions are removed or cannot be sampled, the EGFR status of the metastatic lesions are the potential alternative method to reflect EGFR mutations in the primary NSCLC lesions. This review aimed to evaluate the potential of magnetic resonance imaging (MRI) radiomics based on extrapulmonary metastases in predicting EGFR mutations through a systematic reviews and meta-analysis.</p><p><strong>Materials and methods: </strong>A systematic review of the studies on MRI radiomics based on extrapulmonary metastases in predicting EGFR mutations. The area under the curve (AUC), sensitivity (SNEC), and specificity (SPEC) of each study were separately extracted for comprehensive evaluation of MRI radiomics in predicting EGFR mutations in primary or metastatic NSCLC.</p><p><strong>Results: </strong>Thirteen studies were ultimately included, with 2369 cases of metastatic NSCLC, including five studies predicting EGFR mutations in primary NSCLC, eight studies predicting EGFR mutations in metastatic NSCL. In terms of EGFR mutations in the primary lesion of NSCLC, the pooled AUC was 0.90, with SENC and SPEC of 0.80 and 0.85, respectively, which seems superior to the radiomics meta-analysis based on NSCLC primary lesions. In terms of EGFR mutations in NSCLC metastases, the pooled AUC was 0.86, with SENC and SEPC of 0.79 and 0.79, respectively, indicating moderate evaluation performance.</p><p><strong>Conclusions: </strong>MRI radiomics helps to predict the EGFR mutation status in the primary or metastatic lesions of NSCLC, serve as a high-precision supplement to current molecular detection methods.</p>","PeriodicalId":8927,"journal":{"name":"BioMedical Engineering OnLine","volume":"24 1","pages":"4"},"PeriodicalIF":2.9,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11742221/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142998012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accuracy evaluation and clinical realization of digital interproximal enamel reduction for orthodontics: a case study.","authors":"Jia You, Xiangyu Zhou, Xiaofan Xia, Jianxing Zhang, Yunfeng Liu","doi":"10.1186/s12938-025-01329-0","DOIUrl":"10.1186/s12938-025-01329-0","url":null,"abstract":"<p><strong>Objective: </strong>This study presents a novel digital interproximal enamel reduction (IER) clinical procedure, aiming to improve the effectiveness of IER processes in orthodontic treatment.</p><p><strong>Methods: </strong>A malocclusion case of skeletal-class I and angle-class I was selected for the experimental investigation. A three-dimensional (3D) model of the dentition was constructed using scanning data from a plaster model. The IER volume was measured by the overlay area of two neighboring crowns on the arranged virtual teeth. For the upper dentition, a guide plate was innovatively designed based on the original surface of the dentition and the calculated IER volume. The guide plate was fabricated using stereolithography 3D printing (SLA), and was successfully employed during the IER operation. For the lower dentition, the IER procedure was performed using the free-hand method, guided by the predesigned IER volume. Preoperative and postoperative 3D models of the dentition were compared to assess the accuracy of both IER methods.</p><p><strong>Results: </strong>The standard deviation of upper dentition IER with guide plate was calculated as 0.13 mm, while that of lower dentition IER by freehand was 0.24 mm.</p><p><strong>Conclusion: </strong>Through the integration of laser scanning, 3D reconstruction, virtual arrangement, guide plate design, and 3D printing, this study not only explores a novel digital IER method, but also demonstrates its clinical applicability. The findings provide compelling evidence of the method's superior accuracy in clinical practice, offering a new approach for high-precision IER operations in orthodontic treatment.</p>","PeriodicalId":8927,"journal":{"name":"BioMedical Engineering OnLine","volume":"24 1","pages":"1"},"PeriodicalIF":2.9,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11737072/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142999528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}