Computer Methods in Biomechanics and Biomedical Engineering最新文献_第6页

Revolutionizing Breast Cancer Care: AI-Enhanced Diagnosis and Patient History. 彻底改变乳腺癌护理：人工智能增强诊断和患者病史。

IF 1.7 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-04-01 Epub Date: 2024-01-04 DOI: 10.1080/10255842.2023.2300681

Maleeha Fathima, Mohammed Moulana

{"title":"Revolutionizing Breast Cancer Care: AI-Enhanced Diagnosis and Patient History.","authors":"Maleeha Fathima, Mohammed Moulana","doi":"10.1080/10255842.2023.2300681","DOIUrl":"10.1080/10255842.2023.2300681","url":null,"abstract":"Breast cancer poses a significant global health challenge, demanding enhanced diagnostic accuracy and streamlined medical history documentation. This study presents a holistic approach that harnesses the power of artificial intelligence (AI) and machine learning (ML) to address these pressing needs. This study presents a comprehensive methodology for breast cancer diagnosis and medical history generation, integrating data collection, feature extraction, machine learning, and AI-driven history-taking. The research employs a systematic approach to ensure accurate diagnosis and efficient history collection. Data preprocessing merges similar attributes to streamline analysis. Three key algorithms, Support Vector Machine (SVM), K-Nearest Neighbours (KNN), and Fuzzy Logic, are applied. Fuzzy Logic shows exceptional accuracy in handling uncertain data. Deep learning models enhance predictive accuracy, emphasizing the synergy between traditional and deep learning approaches. The AI-driven history collection simplifies the patient history-taking process, adapting questions dynamically based on patient responses. Comprehensive medical history reports summarize patient data, facilitating informed healthcare decisions. The research prioritizes ethical compliance and data privacy. OpenAI has integrated GPT-3.5 to generate automated patient reports, offering structured overviews of patient health history. The study's results indicate the potential for enhanced disease prediction accuracy and streamlined medical history collection, contributing to more reliable healthcare assessments and patient care. Machine learning, deep learning, and AI-driven approaches hold promise for a wide range of applications, particularly in healthcare and beyond.","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"642-654"},"PeriodicalIF":1.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139099053","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

A scale conjugate neural network approach for the fractional schistosomiasis disease system. 分型血吸虫病系统的尺度共轭神经网络方法。

IF 1.7 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-04-01 Epub Date: 2023-12-26 DOI: 10.1080/10255842.2023.2298717

Zulqurnain Sabir, Shahid Ahmad Bhat, Muhammad Asif Zahoor Raja, Dumitru Baleanu, Fazli Amin, Hafiz Abdul Wahab

{"title":"A scale conjugate neural network approach for the fractional schistosomiasis disease system.","authors":"Zulqurnain Sabir, Shahid Ahmad Bhat, Muhammad Asif Zahoor Raja, Dumitru Baleanu, Fazli Amin, Hafiz Abdul Wahab","doi":"10.1080/10255842.2023.2298717","DOIUrl":"10.1080/10255842.2023.2298717","url":null,"abstract":"This study presents the numerical solutions of the fractional schistosomiasis disease model (SDM) using the supervised neural networks (SNNs) and the computational scaled conjugate gradient (SCG), i.e. SNNs-SCG. The fractional derivatives are used for the precise outcomes of the fractional SDM. The preliminary fractional SDM is categorized as: uninfected, infected with schistosomiasis, recovered through infection, expose and susceptible to this virus. The accurateness of the SNNs-SCG is performed to solve three different scenarios based on the fractional SDM with synthetic data obtained with fractional Adams scheme (FAS). The generated data of FAS is used to execute SNNs-SCG scheme with 81% for training samples, 12% for testing and 7% for validation or authorization. The correctness of SNNs-SCG approach is perceived by the comparison with reference FAS results. The performances based on the error histograms (EHs), absolute error, MSE, regression, state transitions (STs) and correlation accomplish the accuracy, competence, and finesse of the SNNs-SCG scheme.","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"614-627"},"PeriodicalIF":1.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139040855","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

Mechanical property of Ti6Al4V cylindrical porous structure for dental implants fabricated by selective laser melting. 利用选择性激光熔化技术制造的用于牙科植入物的 Ti6Al4V 圆柱形多孔结构的力学性能。

IF 1.7 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-04-01 Epub Date: 2024-01-04 DOI: 10.1080/10255842.2023.2300686

Yun Zhai, Hao Zhang, Tong Liu, Cong Zou, Changchun Zhou

{"title":"Mechanical property of Ti6Al4V cylindrical porous structure for dental implants fabricated by selective laser melting.","authors":"Yun Zhai, Hao Zhang, Tong Liu, Cong Zou, Changchun Zhou","doi":"10.1080/10255842.2023.2300686","DOIUrl":"10.1080/10255842.2023.2300686","url":null,"abstract":"The commonly used titanium alloy dental implants currently apply solid structures. However, issues such as stress shielding and stress concentration may arise due to the significant difference in elastic modulus between the implant and host. In order to address these problems, this paper proposes five porous structures based on the Gibson-Ashby theoretical model. We utilized selective laser melting technology to shape a porous structure using Ti-6Al-4V material precisely. The mechanical properties of the porous structure were verified through simulation and compression experiments. The optimal porous structure, which best matched the human bone, was a circular ring structure with a pillar diameter of 0.6 mm and a layer height of 2 mm. The stress and strain of the porous implant on the surrounding cortical and cancellous bone under different biting conditions were studied to verify the effectiveness of the optimal circular ring porous structure in alleviating stress shielding in both standard and osteoporotic bone conditions. The results confirm that the circular ring porous structure meets implant requirements and provides a theoretical basis for clinical dental implantation.","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"679-697"},"PeriodicalIF":1.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139099140","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

Computer-assisted interpretation, in-depth exploration and single cell type annotation of RNA sequence data using k-means clustering algorithm. 利用 k-means 聚类算法对 RNA 序列数据进行计算机辅助解释、深入探索和单细胞类型注释。

IF 1.7 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-04-01 Epub Date: 2024-01-18 DOI: 10.1080/10255842.2023.2300685

Pranshu Saxena, Amit Sinha, Sanjay Kumar Singh

{"title":"Computer-assisted interpretation, in-depth exploration and single cell type annotation of RNA sequence data using k-means clustering algorithm.","authors":"Pranshu Saxena, Amit Sinha, Sanjay Kumar Singh","doi":"10.1080/10255842.2023.2300685","DOIUrl":"10.1080/10255842.2023.2300685","url":null,"abstract":"At now, the majority of approaches rely on manual techniques for annotating cell types subsequent to clustering the data obtained from single-cell RNA sequencing (scRNA-seq). These approaches require a significant amount of physical exertion and depend substantially on the user's skill, perhaps resulting in uneven outcomes and inconsistency in treatment. In this paper, we provide a computer-assisted interpretation of every single cell of a tissue sample, along with an in-depth exploration of an individual cell's molecular, phenotypic and functional attributes. The paper will also perform k-means clustering followed by silhouette validation based on similar phenotype and functional attributes, and also, cell type annotation is performed, where we match a cell's gene profile against some known database by applying certain statistical conditions. Finally, all the genes are mapped spatially on the tissue sample. This paper is an aid to medicine to know which cells are expressed/not expressed in a tissue sample and their spatial location on the tissue sample.","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"668-678"},"PeriodicalIF":1.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139486703","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

CNN-based diagnosis model of children's bladder compliance using a single intravesical pressure signal. 利用单一膀胱内压力信号建立基于 CNN 的儿童膀胱顺应性诊断模型。

IF 1.7 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-04-01 Epub Date: 2024-01-09 DOI: 10.1080/10255842.2023.2301414

Gang Yuan, Zicong Ge, Jian Zheng, Xiangming Yan, Mingcui Fu, Ming Li, Xiaodong Yang, Liangfeng Tang

引用次数: 0

A pooling convolution model for multi-classification of ECG and PCG signals. 用于心电图和 PCG 信号多重分类的集合卷积模型。

IF 1.7 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-04-01 Epub Date: 2024-01-09 DOI: 10.1080/10255842.2023.2299697

Juliang Wang, Junbin Zang, Qi An, Haoxin Wang, Zhidong Zhang

{"title":"A pooling convolution model for multi-classification of ECG and PCG signals.","authors":"Juliang Wang, Junbin Zang, Qi An, Haoxin Wang, Zhidong Zhang","doi":"10.1080/10255842.2023.2299697","DOIUrl":"10.1080/10255842.2023.2299697","url":null,"abstract":"Electrocardiogram (ECG) and phonocardiogram (PCG) signals are physiological signals generated throughout the cardiac cycle. The application of deep learning techniques to recognize ECG and PCG signals can greatly enhance the efficiency of cardiovascular disease detection. Therefore, we propose a series of straightforward and effective pooling convolutional models for the multi-classification of ECG and PCG signals. Initially, these signals undergo preprocessing. Subsequently, we design various structural blocks, including a stacked block (MCM) comprising convolutional layer and max-pooling layers, along with its variations, as well as a residual block (REC). By adjusting the number of structural blocks, these models can handle ECG and PCG data with different sampling rates. In the final tests, the models utilizing the MCM structural block achieved accuracies of 98.70 and 92.58% on the ECG and PCG fusion datasets, respectively. These accuracies surpass those of all networks utilizing its variations. Moreover, compared to the models employing the REC structural block, the accuracies are improved by 0.02 and 4.30%, respectively. Furthermore, this research has been validated through tests conducted on multiple ECG and PCG datasets, along with comparisons to other published literature. To further validate the generalizability of the model, an additional experiment involving the classification of a synchronized ECG-PCG dataset was conducted. This dataset is divided into seven different levels of fatigue based on the amount of exercise performed by each healthy subject during the testing process. The results indicate that the model using the MCM block also achieved the highest accuracy.","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"628-641"},"PeriodicalIF":1.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139405106","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

Advancing cancer care: unravelling genomic insights for precision medicine using meticulous predictive architecture. 推进癌症护理：利用细致的预测架构揭示精准医学的基因组见解。

IF 1.7 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-03-31 DOI: 10.1080/10255842.2025.2477809

Swati B Bhonde, Sharmila K Wagh, Jayashree R Prasad

引用次数: 0

Compensatory behaviours after oral cancer: stretch reflex improves simulated tongue protrusion. 口腔癌后的代偿行为：伸展反射改善模拟舌突。

IF 1.7 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-03-27 DOI: 10.1080/10255842.2025.2482128

Noor Al-Zanoon, Jacqueline Cummine, Caroline C Jeffery, Daniel Aalto

引用次数: 0

Maximizing cycling efficiency: innovative bicycle drive mechanisms tailored to individual muscular capacities. 最大限度地提高自行车效率：创新的自行车驱动机制量身定制的个人肌肉能力。

IF 1.7 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-03-25 DOI: 10.1080/10255842.2025.2482894

Sabrina Otmani, Andrew Murray, Christine Azevedo Coste, François Bailly

{"title":"Maximizing cycling efficiency: innovative bicycle drive mechanisms tailored to individual muscular capacities.","authors":"Sabrina Otmani, Andrew Murray, Christine Azevedo Coste, François Bailly","doi":"10.1080/10255842.2025.2482894","DOIUrl":"https://doi.org/10.1080/10255842.2025.2482894","url":null,"abstract":"This study explores the customization and optimization of three distinct bicycle drive mechanisms, leveraging an individual's biomechanical data to maximize pedaling power throughput. Our approach utilizes torque/velocity/position relationships of the hip and the knee, so that the kinematics of the optimized designs allow the user to pedal with maximized joint torques and thus, enhance the power produced at the crank. The method is applied to the cases of two users with significantly distinct anthropometries, showing noticeable changes in the drive mechanisms and demonstrating its effectiveness for personalizing bicycle designs. The study highlights the importance of considering individual biomechanical factors, showing that even slight variations in design can lead to changes in the cycling kinematics, resulting in improved performance. Simulation results also show increased mean power throughput for more complex drive mechanisms compared to a classical one, regardless of the user profile. This suggests that such designs should be capable of accommodating a range of cyclists, from recreational users to high-performance athletes, as well as individuals and athletes with motor impairments. These findings underline the potential of biomechanically-informed personalized bicycle drive mechanisms to optimize pedaling efficiency and enhance performance across diverse user groups.","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-10"},"PeriodicalIF":1.7,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143711973","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

Motor imagery EEG microstates are influenced by alpha power. 运动想象的脑电图微观状态受阿尔法功率的影响。

IF 1.7 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-03-24 DOI: 10.1080/10255842.2025.2476185

Xin Xiong, Xiaoyu Ji, Sanli Yi, Chunwu Wang, Ruixiang Liu, Jianfeng He

{"title":"Motor imagery EEG microstates are influenced by alpha power.","authors":"Xin Xiong, Xiaoyu Ji, Sanli Yi, Chunwu Wang, Ruixiang Liu, Jianfeng He","doi":"10.1080/10255842.2025.2476185","DOIUrl":"https://doi.org/10.1080/10255842.2025.2476185","url":null,"abstract":"Electroencephalogram (EEG) microstates are pivotal in understanding brain dynamics, reflecting transitions between global states. These parameters undergo selective inhibition within cortical areas, modulated by alpha oscillations. This study investigates how alpha band power influences microstate parameters across various task conditions, including resting state, actual motor execution, and imagined motor tasks. By comparing these three conditions, we aim to elucidate the distinct effects of alpha power on microstate dynamics, as each condition represents a unique pattern of brain activity. Motor imagery (MI) induces event-related desynchronization/synchronization, modulating Mu (alpha) and Beta rhythms in sensorimotor areas. However, the relationship between MI-EEG microstates and alpha power remains unclear. Our results show that alpha power was highest in resting state, followed by imagined motion, and lowest during actual motion. As alpha power increased, microstate A parameters in resting state (occurrence, coverage) decreased, while those in actual motion increased. Additionally, microstate B parameters rose with alpha power in resting state but decreased during imagined motion. Notably, alpha power correlated more strongly with microstate parameters in task states than in resting state. In addition, alpha, theta, and beta powers during task performance were negatively correlated with the duration of microstates A, B, and C, while being positively correlated with the occurrence of microstates A, B, C, and D. These findings suggest that alpha power influences microstate parameters differently depending on the brain, underscoring the significance of inter-band interactions in shaping microstate dynamics.","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-16"},"PeriodicalIF":1.7,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143694023","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