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Dynamic feature selection and quantum representation for precise heart disease prediction: Quantum-HeartDiseaseNet approach. 用于精确心脏病预测的动态特征选择和量子表示：量子心脏疾病网方法。
IF 1.6 4区 医学
Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2026-05-01 Epub Date: 2025-02-05 DOI: 10.1080/10255842.2025.2456990
Liza M Kunjachen, R Kavitha
{"title":"Dynamic feature selection and quantum representation for precise heart disease prediction: Quantum-HeartDiseaseNet approach.","authors":"Liza M Kunjachen, R Kavitha","doi":"10.1080/10255842.2025.2456990","DOIUrl":"10.1080/10255842.2025.2456990","url":null,"abstract":"<p><p>Cardiovascular disease is a leading cause of mortality, necessitating early and precise prediction for improved patient outcomes. This study proposes Quantum-HeartDiseaseNet, a novel heart disease risk prediction framework that integrates a Dynamic Opposite Pufferfish Optimization Algorithm for feature selection and a Quantum Attention-based Bidirectional Gated Recurrent Unit (QABiGRU) for accurate diagnosis. The feature selection method enhances diagnosis accuracy while reducing dimensionality, and Synthetic Minority Oversampling Technique (SMOTE) addresses data imbalance. Evaluated on three heart disease datasets, the proposed model achieved 98.87% accuracy, 98.74% precision, and 98.56% recall, outperforming conventional methods. Experimental results validate its effectiveness in early disease prediction.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1700-1721"},"PeriodicalIF":1.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143257307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Non-Newtonian lacuno-canalicular fluid flow in bone altered by mechanical loading and magnetic field. 机械载荷和磁场对骨内非牛顿腔管流体流动的影响。
IF 1.6 4区 医学
Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2026-05-01 Epub Date: 2025-01-31 DOI: 10.1080/10255842.2025.2453924
Rakesh Kumar, Suja Laxmikant Vajire, Abhishek Kumar Tiwari, Dharmendra Tripathi
{"title":"Non-Newtonian lacuno-canalicular fluid flow in bone altered by mechanical loading and magnetic field.","authors":"Rakesh Kumar, Suja Laxmikant Vajire, Abhishek Kumar Tiwari, Dharmendra Tripathi","doi":"10.1080/10255842.2025.2453924","DOIUrl":"10.1080/10255842.2025.2453924","url":null,"abstract":"<p><p>As humans age, they experience deformity and a decrease in their bone strength, such brittleness in the bones ultimately lead to bone fracture. Magnetic field exposure combined with physical exercise may be useful in mitigating age-related bone loss by improving the canalicular fluid motion within the bone's lacuno-canalicular system (LCS). Nevertheless, an adequate amount of fluid induced shear stress is necessary for the bone mechano-transduction and solute transport in the case of brittle bone diseases. The underlying mechanisms of how magnetic fields, in combination to mechanical loading, affects the canalicular fluid motion still need to be explored. Accordingly, this study aims to develop a computer model to investigate the role of magnetic fields on loading-induced canalicular fluid flow in a curvy lacunar canalicular space with irregular osteocyte cell processes and walls. Moreover, this study considers canalicular fluid as non-Newtonian fluid, i.e., Jeffery fluid. In addition, a machine learning model was further employed for the estimation of parameters which significantly influence the canalicular fluid flow in response to loading and magnetic field. The results show that static magnetic field modulates the loading-induced canalicular fluid flow. Additionally, present study accelerates the fluid induced wall shear stress in case of osteoporosis.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1539-1557"},"PeriodicalIF":1.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143069382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Intraoperative interaction modeling between surgical instruments and soft tissues in neurosurgery based on energy functions. 基于能量函数的神经外科手术器械与软组织的术中互动模型。
IF 1.6 4区 医学
Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2026-05-01 Epub Date: 2024-11-25 DOI: 10.1080/10255842.2024.2431892
Ting Wang, Jilin Wang, Zhenxing Li, Dominik M Ramík, Xiangjun Ji, Ramon Moreno, Xiaorui Zhang, Chiyuan Ma
{"title":"Intraoperative interaction modeling between surgical instruments and soft tissues in neurosurgery based on energy functions.","authors":"Ting Wang, Jilin Wang, Zhenxing Li, Dominik M Ramík, Xiangjun Ji, Ramon Moreno, Xiaorui Zhang, Chiyuan Ma","doi":"10.1080/10255842.2024.2431892","DOIUrl":"10.1080/10255842.2024.2431892","url":null,"abstract":"<p><p>A physical model of soft tissue that provides realistic and real-time haptic and visual feedback is crucial for neurosurgical procedures. This paper investigates the interaction between surgical instruments and soft brain tissue, proposing a soft tissue deformation simulation method based on the principle of energy minimization and constrained energy function. The model includes a permanent deformation energy function induced by friction and a volume preservation energy function to more accurately depict tissue response during procedures such as resection of convex meningiomas and evacuation of intracerebral hematomas. Experimental results show that the proposed method meets the requirements of neurosurgical simulation.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1283-1297"},"PeriodicalIF":1.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142717647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Prognostics of the knee osteoarthritis induced by cyclic loading activities. A model-based analysis. 循环负荷活动诱发膝骨关节炎的预后。基于模型的分析。
IF 1.6 4区 医学
Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2026-05-01 Epub Date: 2025-01-27 DOI: 10.1080/10255842.2025.2456993
Fatima Zahra Mekrane, Radouane Ouladsine, Abdelwahed Barkaoui, Raymond Ghandour
{"title":"Prognostics of the knee osteoarthritis induced by cyclic loading activities. A model-based analysis.","authors":"Fatima Zahra Mekrane, Radouane Ouladsine, Abdelwahed Barkaoui, Raymond Ghandour","doi":"10.1080/10255842.2025.2456993","DOIUrl":"10.1080/10255842.2025.2456993","url":null,"abstract":"<p><p>Repetitive mechanical stresses on the knee joint during daily activities accumulate fatigue damage in the articular cartilage (AC), leading to wear and knee osteoarthritis (KOA). Effective treatments remain limited, underscoring the need for predictive approaches to identify KOA early. This study proposes a mathematical model to estimate AC degradation under cyclic loading from walking. By integrating Miner's rule, Monte Carlo simulations, and Weibull distributions, the model predicts remaining cycles before AC loses 60% of its volume, a critical KOA threshold. Verified against a well-established model, it offers potential for personalized strategies to prevent or delay KOA progression.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1722-1735"},"PeriodicalIF":1.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143054285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
OpenOFM: an open-source implementation of the multi-segment Oxford Foot Model. OpenOFM：多段牛津足模型的开源实现。
IF 1.6 4区 医学
Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2026-05-01 Epub Date: 2025-02-04 DOI: 10.1080/10255842.2024.2448558
Philippe C Dixon, Elodie E Drew, Sean P McBride, Marian Harrington, Julie Stebbins, Amy B Zavatsky
{"title":"OpenOFM: an open-source implementation of the multi-segment Oxford Foot Model.","authors":"Philippe C Dixon, Elodie E Drew, Sean P McBride, Marian Harrington, Julie Stebbins, Amy B Zavatsky","doi":"10.1080/10255842.2024.2448558","DOIUrl":"10.1080/10255842.2024.2448558","url":null,"abstract":"<p><p>The Oxford Foot Model (OFM) is a widely-used multi-segment foot model for the evaluation of foot motion. To date, custom code based on the original scientific publications have failed to reproduce results available through the Vicon plug-in (ViconOFM). This highlights a lack of transparency, affecting the accessibility and understanding of the model. Therefore, the aims of this study are to (1) replicate ViconOFM using Python for open-source distribution (openOFM v1.0) and (2) reproduce the original scientific description of the OFM in a second version (openOFM v1.1), highlighting differences between both versions. A dataset comprising one healthy adult and a set of five patients with heterogeneous foot pathologies was used for analyses. Evaluation was conducted using the normalised root mean square error (NRMSE) between the inter-segment angles and arch heights of both implementations. The openOFM v1.1 was developed based on the original OFM publications. The average NRMSE between ViconOFM and openOFM v1.0, using both healthy and pathological gait, was of 0.0012. Based on our openOFM v1.1 implementation, differences between ViconOFM and the original OFM description from the literature are due to an integrated smoothing and gap filling function and changes in segment definitions. The negligible differences between ViconOFM and openOFM v1.0 in healthy and pathological gait supports the concurrent validity of openOFM. Providing users with both openOFM versions enables informed use of either model and allows further investigation into the implications of these differences. The open-source nature of the project promotes further development.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1478-1491"},"PeriodicalIF":1.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143123634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Identification of circadian rhythm-related biomarkers and development of diagnostic models for Crohn's disease using machine learning algorithms. 使用机器学习算法识别与昼夜节律相关的生物标志物并开发克罗恩病的诊断模型。
IF 1.6 4区 医学
Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2026-05-01 Epub Date: 2025-01-21 DOI: 10.1080/10255842.2025.2453922
Zhijing Zhao, Xia Chen, Qian Xiang, Liu Liu, Xiaohua Li, Boyun Qiu
{"title":"Identification of circadian rhythm-related biomarkers and development of diagnostic models for Crohn's disease using machine learning algorithms.","authors":"Zhijing Zhao, Xia Chen, Qian Xiang, Liu Liu, Xiaohua Li, Boyun Qiu","doi":"10.1080/10255842.2025.2453922","DOIUrl":"10.1080/10255842.2025.2453922","url":null,"abstract":"<p><p>The global rise in Crohn's Disease (CD) incidence has intensified diagnostic challenges. This study identified circadian rhythm-related biomarkers for CD using datasets from the GEO database. Differentially expressed genes underwent Weighted Gene Co-Expression Network Analysis, with 49 hub genes intersected from GeneCards data. Diagnostic models were constructed using machine learning algorithms, and biologic therapy efficacy was predicted with advanced regression techniques. Single-cell sequencing showed high gene expression in stem cells, immune, and endothelial cells, with validation confirming significant differences between CD patients and controls. These findings suggest circadian rhythm-related genes as promising diagnostic biomarkers for CD.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1522-1538"},"PeriodicalIF":1.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143015677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
MSCNet-FS: development of intelligent epileptic seizure anticipation model by multi serial cascaded network with feature Specific using scalogram images of EEG signal. MSCNet-FS：利用脑电信号的尺度图图像，开发具有特征的多串级联网络智能癫痫发作预测模型。
IF 1.6 4区 医学
Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2026-05-01 Epub Date: 2024-12-02 DOI: 10.1080/10255842.2024.2431886
Vinod J Thomas, Anto Sahaya Dhas
{"title":"MSCNet-FS: development of intelligent epileptic seizure anticipation model by multi serial cascaded network with feature Specific using scalogram images of EEG signal.","authors":"Vinod J Thomas, Anto Sahaya Dhas","doi":"10.1080/10255842.2024.2431886","DOIUrl":"10.1080/10255842.2024.2431886","url":null,"abstract":"<p><p>The early stage of the Epileptic Seizure Anticipation (ESA) model plays a significant part in supplying accurate medical care. In this research work, a novel Multi Serial Cascaded Network with Feature Specific model is developed. The scalogram images are given as input to a developed model. Here, the Target Feature Selection is performed optimally using the Improved Fitness Value Index-Archimedes Optimization (IFVI-AO) Algorithm. Finally, the selections of accurate features are subjected to 'Bi-directional Long Short-Term Memory (Bi-LSTM)'. The implemented model is validated and provides timely results to detect epileptic seizure disorder.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1259-1282"},"PeriodicalIF":1.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142774417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The biomechanical injury calculator: a postprocessor software for a finite element human body model. 生物力学损伤计算器：一种有限元人体模型的后处理软件。
IF 1.6 4区 医学
Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2026-05-01 Epub Date: 2025-04-23 DOI: 10.1080/10255842.2024.2448554
Srihari Menon, Quenton Hua, Nancy J Currie-Gregg
{"title":"The biomechanical injury calculator: a postprocessor software for a finite element human body model.","authors":"Srihari Menon, Quenton Hua, Nancy J Currie-Gregg","doi":"10.1080/10255842.2024.2448554","DOIUrl":"10.1080/10255842.2024.2448554","url":null,"abstract":"<p><p>An injury risk assessment postprocessor for the Global Human Body Model Consortium (GHBMC) model is presented. The Biomechanical Injury Calculator (BIC) calculates injury probabilities for the head, neck, spine, and pelvis post-simulation, along with a total injury probability for the entire complex. It also generates an injury heatmap. Developed for the GHBMC M50-OS v2.3 +DeformSpine, BIC was validated by comparing 103 airmen's seat ejection injuries to BIC-predicted injury probabilities in 30 vertical seat load simulations. Observed injury rates correlated strongly with BIC predictions (Spearman=0.943, Pearson=0.982) within 5.16% margin. The total injury probability of 58.48% closely matched the 56.3% observed rate.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1419-1431"},"PeriodicalIF":1.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144044113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Predicting nanofluid behavior in inflamed stenotic arteries: a neural network and finite element-Based analysis. 预测发炎狭窄动脉中的纳米流体行为：基于神经网络和有限元的分析。
IF 1.6 4区 医学
Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2026-05-01 Epub Date: 2025-01-21 DOI: 10.1080/10255842.2025.2453926
Yasir Ul Umair Bin Turabi, Shafee Ahmad, Shams Ul Islam, Zahir Shah, Narcisa Vrinceanu, Mihaela Racheriu
{"title":"Predicting nanofluid behavior in inflamed stenotic arteries: a neural network and finite element-Based analysis.","authors":"Yasir Ul Umair Bin Turabi, Shafee Ahmad, Shams Ul Islam, Zahir Shah, Narcisa Vrinceanu, Mihaela Racheriu","doi":"10.1080/10255842.2025.2453926","DOIUrl":"10.1080/10255842.2025.2453926","url":null,"abstract":"<p><p>This study examines heat transfer and nanofluid-enhanced blood flow behaviour in stenotic arteries under inflammatory conditions, addressing critical challenges in cardiovascular health. The blood, treated as a Newtonian fluid, is augmented with gold nanoparticles to improve thermal conductivity and support drug delivery applications. A hybrid methodology combining finite element method (FEM) for numerical modelling and artificial neural networks (ANN) for stability prediction provides a robust analytical framework. Parametric analysis reveals that increasing stenosis severity (60% to 80%) results in a 45% enhancement in heat transfer, demonstrating the efficacy of nanoparticle integration. The results show that the size of the vortices decreases due to the position changing of the upper stenoses, whereas it rises with increasing stenosis peak. Higher nanoparticle volume fraction (<math><mrow><mi>ϕ</mi></mrow></math>) amplifies momentum diffusion, resulting in larger vortices, while improved thermal conductivity enhances heat transfer. Inflammation significantly affects flow patterns and heat transport with important implications in treating cardiovascular disorders and biological applications. The regression analysis confirms a close match between predicted and target data, showcasing the robustness of the FEM-ANN hybrid approach for modelling biofluid systems.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1573-1593"},"PeriodicalIF":1.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143015679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Comparative analysis of airflow dynamics and sputum expulsion during cough in healthy and bronchial stenosis respiratory tract. 健康与支气管狭窄呼吸道咳嗽时气流动力学及排痰的比较分析。
IF 1.6 4区 医学
Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2026-05-01 Epub Date: 2025-01-18 DOI: 10.1080/10255842.2025.2453925
Mingqian Mao, Zhichen Yang, Xiaoyu Ni, Changwang Pan
{"title":"Comparative analysis of airflow dynamics and sputum expulsion during cough in healthy and bronchial stenosis respiratory tract.","authors":"Mingqian Mao, Zhichen Yang, Xiaoyu Ni, Changwang Pan","doi":"10.1080/10255842.2025.2453925","DOIUrl":"10.1080/10255842.2025.2453925","url":null,"abstract":"<p><p>Bronchial stenosis impacts cough mechanisms and respiratory function. This study used MIMICS and Fluent to construct and simulate a 3D airway model of an elderly female patient with bronchial stenosis. Utilizing dynamic mesh and fluid-structure interaction, airflow during coughing was analyzed, including velocity, wall shear stress, and deformation. The Eulerian wall film model quantified sputum dynamics, revealing that stenosis increases shear stress, exacerbates deformation, and reduces sputum expulsion efficiency, particularly for medium to high viscosity sputum. These findings deepen understanding of bronchial stenosis pathophysiology and offer insights for improving diagnosis, treatment, and prevention of respiratory diseases.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1558-1572"},"PeriodicalIF":1.6,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143015676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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