Computers in biology and medicine最新文献_第10页

Musculoskeletal model predictions sensitivity to upper body mass scaling during gait.

IF 7 2区医学

Computers in biology and medicine Pub Date : 2025-03-01 Epub Date: 2025-01-27 DOI: 10.1016/j.compbiomed.2025.109739

Abdul Aziz Vaqar Hulleck, Muhammad Abdullah, AbdelSalam Tareq Alkhalaileh, Tao Liu, Dhanya Menoth Mohan, Rateb Katmah, Kinda Khalaf, Marwan El-Rich

{"title":"Musculoskeletal model predictions sensitivity to upper body mass scaling during gait.","authors":"Abdul Aziz Vaqar Hulleck, Muhammad Abdullah, AbdelSalam Tareq Alkhalaileh, Tao Liu, Dhanya Menoth Mohan, Rateb Katmah, Kinda Khalaf, Marwan El-Rich","doi":"10.1016/j.compbiomed.2025.109739","DOIUrl":"10.1016/j.compbiomed.2025.109739","url":null,"abstract":"<p><p>Musculoskeletal modeling based on inverse dynamics provides a cost-effective non-invasive means for calculating intersegmental joint reaction forces and moments, solely relying on kinematic data, easily obtained from smart wearables. On the other hand, the accuracy and precision of such models strongly hinge upon the selected scaling methodology tailored to subject-specific data. This study investigates the impact of upper body mass distribution on internal and external kinetics computed using a comprehensive musculoskeletal model during level walking in both normal weight and obese individuals. Human motion data was collected using seventeen body worn inertial measuring units for nineteen (19) healthy subjects. The results indicate that variations in segmental masses and centers of mass, resulting from diverse mass scaling techniques, significantly affect ground reaction force estimations in obese subjects, particularly in the vertical component, with a root mean square error (RMSE) of 54.7 ± 23.8 %BW; followed by 12.3 ± 8.0 %BW (medio-lateral); and 6.2 ± 3.2 %BW (antero-posterior). The vertical component of hip, knee, and ankle joint reaction forces also exhibit sensitivity to personalized mass distribution variations. Importantly, the degree of deviation in model predictions increases with body mass index. Statistical analysis using single sample Wilcoxon-Signed Rank test for non-normal data and t-test for normal data, revealed significant differences (p < 0.05) in the computed errors in kinetic parameters between the two scaling approaches. The body shape-based scaling approach significantly impacts musculoskeletal modeling in clinical applications where the upper body mass distribution is crucial, such as in spinal deformities, obesity, and low back pain. This approach accounts for the body shape inherent variability within the same BMI category and enhances the predicted joint kinetics.</p>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"186 ","pages":"109739"},"PeriodicalIF":7.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143058356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 comprehensive scoping review on machine learning-based fetal echocardiography analysis. 基于机器学习的胎儿超声心动图分析综述。

IF 7 2区医学

Computers in biology and medicine Pub Date : 2025-03-01 Epub Date: 2025-01-15 DOI: 10.1016/j.compbiomed.2025.109666

Netzahualcoyotl Hernandez-Cruz, Olga Patey, Clare Teng, Aris T Papageorghiou, J Alison Noble

引用次数: 0

Adaptive sequence alignment for metagenomic data analysis.

IF 7 2区医学

Computers in biology and medicine Pub Date : 2025-03-01 Epub Date: 2025-01-26 DOI: 10.1016/j.compbiomed.2025.109743

Sami Pietilä, Tomi Suomi, Niklas Paulin, Asta Laiho, Yannes S Sclivagnotis, Laura L Elo

{"title":"Adaptive sequence alignment for metagenomic data analysis.","authors":"Sami Pietilä, Tomi Suomi, Niklas Paulin, Asta Laiho, Yannes S Sclivagnotis, Laura L Elo","doi":"10.1016/j.compbiomed.2025.109743","DOIUrl":"10.1016/j.compbiomed.2025.109743","url":null,"abstract":"<p><p>With advances in sequencing technologies, the use of high-throughput sequencing to characterize microbial communities is becoming increasingly feasible. However, metagenomic assembly poses computational challenges in reconstructing genes and organisms from complex samples. To address this issue, we introduce a new concept called Adaptive Sequence Alignment (ASA) for analyzing metagenomic DNA sequence data. By iteratively adapting a set of partial alignments of reference sequences to match the sample data, the approach can be applied in multiple scenarios, from taxonomic identification to assembly of target regions of interest. To demonstrate the benefits of ASA, we present two application scenarios and compare the results with state-of-the-art methods conventionally used for the same tasks. In the first, ASA accurately detected microorganisms from a sequenced metagenomic sample with a known composition. The second illustrated the utility of ASA in assembling target genetic regions of the microorganisms. An example implementation of the ASA concept is available at https://github.com/elolab/ASA.</p>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"186 ","pages":"109743"},"PeriodicalIF":7.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143051712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Disclosing neonatal pain in real-time: AI-derived pain sign from continuous assessment of facial expressions

IF 7 2区医学

Computers in biology and medicine Pub Date : 2025-03-01 DOI: 10.1016/j.compbiomed.2025.109908

Leonardo Antunes Ferreira , Lucas Pereira Carlini , Gabriel de Almeida Sá Coutrin , Tatiany Marcondes Heiderich , Rita de Cássia Xavier Balda , Marina Carvalho de Moraes Barros , Ruth Guinsburg , Carlos Eduardo Thomaz

{"title":"Disclosing neonatal pain in real-time: AI-derived pain sign from continuous assessment of facial expressions","authors":"Leonardo Antunes Ferreira , Lucas Pereira Carlini , Gabriel de Almeida Sá Coutrin , Tatiany Marcondes Heiderich , Rita de Cássia Xavier Balda , Marina Carvalho de Moraes Barros , Ruth Guinsburg , Carlos Eduardo Thomaz","doi":"10.1016/j.compbiomed.2025.109908","DOIUrl":"10.1016/j.compbiomed.2025.109908","url":null,"abstract":"<div><div>This study introduces an AI-derived pain sign for continuous neonatal pain assessment, addressing the limitations of existing pain scales and computational approaches. Traditional pain scales, though widely used, are hindered by inter-rater variability, discontinuity, and subjectivity. While AI, particularly Deep-Learning, has shown promise, prior research has largely prioritized model performance over clinical applicability, often delivering static, binary predictions that lack interpretability in clinical practice. To bridge this gap, we developed a real-time pain sign tracking tool using facial expression analysis, a primary and non-invasive pain indicator in neonates. Leveraging benchmark datasets (iCOPE, iCOPEvid, and UNIFESP) and Deep-Learning frameworks (VGG-Face, N-CNN, and ViT-B/16), the models analyze video frames to generate a continuous visual representation of pain probability. Our results reveal the limitations of single-label predictions for time intervals, emphasizing the utility of a continuous monitoring visualization tool. The proposed pain sign effectively tracks dynamic changes in neonatal facial expressions, providing actionable and interpretable insights for healthcare professionals. We categorized these insights into a novel classification scheme, such as stable, irregular, unstable, and indeterminate pain signs. By integrating this pain sign into clinical workflows as a potential vital sign, this approach enables personalized pain management and continuous monitoring of both current and historical pain states in neonates, enhancing neonatal care and improving outcomes for these vulnerable patients.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"189 ","pages":"Article 109908"},"PeriodicalIF":7.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143521058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Detection, identification and removing of artifacts from sEMG signals: Current studies and future challenges. 从表面肌电信号中检测、识别和去除伪影：当前研究和未来挑战。

IF 7 2区医学

Computers in biology and medicine Pub Date : 2025-03-01 Epub Date: 2025-01-10 DOI: 10.1016/j.compbiomed.2025.109651

Mohamed Ait Yous, Said Agounad, Siham Elbaz

{"title":"Detection, identification and removing of artifacts from sEMG signals: Current studies and future challenges.","authors":"Mohamed Ait Yous, Said Agounad, Siham Elbaz","doi":"10.1016/j.compbiomed.2025.109651","DOIUrl":"10.1016/j.compbiomed.2025.109651","url":null,"abstract":"<p><p>Surface electromyography (sEMG), a non-invasive technique, offers the ability to identify insights into the activities of muscles in the form of electrical pulses. During the process of recording, the sEMG signals frequently become contaminated by a multitude of different artifacts, the origin of which may be attributed to numerous sources. These artifacts affect the reliability and accuracy of the pure sEMG activity, and subsequently reduce the quality of analysis and interpretation. This can lead to a misinterpretation of sEMG signals, incorrect diagnostic, or a false decision in the case of human-machine interfaces (HMI), etc. Currently, several approaches have been developed to remove or reduce the effect of artifacts on the sEMG activity. In this paper, a comprehensive review of the current studies dealing with identification, detection, and removal of artifacts from sEMG signals is proposed. In addition, this study presents different features used to characterize the artifacts from that of the clean sEMG recordings. Finally, in order to improve the quality of denoising methods, the associated challenges of detection and artifact removal approaches are discussed to be addressed carefully in the future works.</p>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"186 ","pages":"109651"},"PeriodicalIF":7.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142964085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

CA-SQBG: Cross-attention guided Siamese quantum BiGRU for drug-drug interaction extraction.

IF 7 2区医学

Computers in biology and medicine Pub Date : 2025-03-01 Epub Date: 2025-01-25 DOI: 10.1016/j.compbiomed.2025.109655

Ting Zhang, Changqing Yu, Shanwen Zhang

{"title":"CA-SQBG: Cross-attention guided Siamese quantum BiGRU for drug-drug interaction extraction.","authors":"Ting Zhang, Changqing Yu, Shanwen Zhang","doi":"10.1016/j.compbiomed.2025.109655","DOIUrl":"10.1016/j.compbiomed.2025.109655","url":null,"abstract":"<p><p>Accurate and efficient drug-drug interaction extraction (DDIE) from the medical corpus is essential for pharmacovigilance, drug therapy and drug development. To solve the problems of unbalance dataset and lack of accurate manual annotations in DDIE, a cross-attention guided Siamese quantum BiGRU (CA-SQBG) is constructed to improve feature representation learning ability for DDIE. It mainly consists of two quantum BiGRUs (QBiGRUs) and a cross-attention, where two QBiGRUs are Siamese implemented in a variational quantum environment to learn the contextual semantic feature representation of drug pairs, cross-attention is employed to learn mutual information from the Siamese QBiGRUs, which in turn allows the two modules to extract DDI more collaboratively. Unlike BiGRU, Siamese QBiGRUs uses internal and external dependencies in quaternion algebra to map DDI correlations within and between multidimensional features, whereas BiGRU can only capture dependencies within sequences. CA-SQBG is evaluated on the DDIExtraction2013 dataset, and the results demonstrate that it can effectively capture the inter- and intra-dependencies within multimodal features with few parameters, using a small number of training samples, and is superior to the most advanced DDIE methods. CA-SQBG offers potential applications for quantum computing and Siamese networks in the field of DDIE. Code is available on https://github.com/xaycq/CA-SQBG.</p>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"186 ","pages":"109655"},"PeriodicalIF":7.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143045913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Preoperative assessment of patients at risk of postoperative respiratory depression

IF 7 2区医学

Computers in biology and medicine Pub Date : 2025-03-01 DOI: 10.1016/j.compbiomed.2025.109805

Atousa Assadi , Frances Chung , Azadeh Yadollahi

{"title":"Preoperative assessment of patients at risk of postoperative respiratory depression","authors":"Atousa Assadi , Frances Chung , Azadeh Yadollahi","doi":"10.1016/j.compbiomed.2025.109805","DOIUrl":"10.1016/j.compbiomed.2025.109805","url":null,"abstract":"<div><div>Respiratory depression during sleep is a major health challenge after surgery. The main cause is reduction in breathing due to opioids, which are commonly used for management of postoperative pain. The consequences are hypoxemia and hypercapnia, which may increase the risk of cardiovascular complications, mortality, and healthcare utilization. Identifying individuals who are at risk of postoperative respiratory depression prior to the surgery can help guide the perioperative care to reduce adverse outcomes. In this project, we developed a risk assessment model to identify individuals at risk of postoperative respiratory depression prior to the surgery, based on the demographics and changes in preoperative overnight oxyhemoglobin saturation (SpO<sub>2</sub>) levels. To achieve this, we retrospectively analyzed SpO<sub>2</sub> signals of 159 patients, which were recorded continuously preoperatively and on the third night after surgery. Respiratory depression was defined as postoperative episodes where SpO<sub>2</sub> was ≤85% for more than 3 minutes. From preoperative SpO<sub>2</sub> signals, we extracted features to characterize overnight SpO<sub>2</sub> and desaturation episodes. We streamlined a systematic process for feature selection and model development using a nested cross-validation pipeline. Our results indicated that random forest, XGBoost, and Naïve bayes demonstrated the highest predictive performance, consistently surpassing the recent available PRODIGY model. These findings suggest that demographics and preoperative SpO<sub>2</sub> characteristics can preoperatively identify individuals at high-risk of postoperative respiratory depression, which offers a non-invasive and cost-effective method of monitoring respiratory health.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"189 ","pages":"Article 109805"},"PeriodicalIF":7.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143520923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Hemodynamics indicates differences between patients with and without a stroke outcome after left ventricular assist device implantation

IF 7 2区医学

Computers in biology and medicine Pub Date : 2025-03-01 DOI: 10.1016/j.compbiomed.2025.109877

Akshita Sahni , Sreeparna Majee , Jay D. Pal , Erin E. McIntyre , Kelly Cao , Debanjan Mukherjee

{"title":"Hemodynamics indicates differences between patients with and without a stroke outcome after left ventricular assist device implantation","authors":"Akshita Sahni , Sreeparna Majee , Jay D. Pal , Erin E. McIntyre , Kelly Cao , Debanjan Mukherjee","doi":"10.1016/j.compbiomed.2025.109877","DOIUrl":"10.1016/j.compbiomed.2025.109877","url":null,"abstract":"<div><div>Stroke remains a leading cause of complications and mortality in heart failure patients treated with a Left Ventricular Assist Device (LVAD). Hemodynamics plays a central role underlying post-LVAD stroke risk and etiology. Yet, detailed quantitative assessment of hemodynamic variables and their relation to stroke outcomes in patients on LVAD support remains a challenge. Modalities for pre-implantation assessment of post-implantation hemodynamics can help address this challenge. We present an <em>in silico</em> hemodynamics analysis for a digital twin cohort 12 patients on LVAD support; 6 with reported stroke outcomes and 6 without. For each patient we created a post-implant twin with the LVAD outflow graft reconstructed from cardiac-gated CT images; and a pre-implant twin of an estimated baseline flow by removing the LVAD outflow graft and driving flow from the aortic valve opening. Hemodynamics was characterized using descriptors for helical flow, vortex generation, and wall shear stress. We observed higher average values for descriptors of positive helical flow, vortex generation, and wall shear stress, across the 6 cases with stroke outcomes when compared with cases without stroke. When the descriptors for LVAD-driven flow were compared against estimated pre-implantation flow, extent of positive helicity was higher, and vorticity and wall shear were lower in cases with stroke compared to those without. Our study suggests that quantitative analysis of hemodynamics after LVAD implantation; and hemodynamic alterations from a pre-implant flow scenario, can potentially reveal hidden information linked to stroke outcomes during LVAD support. This has broad implications on understanding stroke etiology; and using patient digital twins for LVAD treatment planning, surgical optimization, and efficacy assessment.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"189 ","pages":"Article 109877"},"PeriodicalIF":7.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143520924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

KNU-DTI: KNowledge United Drug-Target Interaction prediction

IF 7 2区医学

Computers in biology and medicine Pub Date : 2025-03-01 DOI: 10.1016/j.compbiomed.2025.109927

Ryong Heo , Dahyeon Lee , Byung Ju Kim , Sangmin Seo , Sanghyun Park , Chihyun Park

{"title":"KNU-DTI: KNowledge United Drug-Target Interaction prediction","authors":"Ryong Heo , Dahyeon Lee , Byung Ju Kim , Sangmin Seo , Sanghyun Park , Chihyun Park","doi":"10.1016/j.compbiomed.2025.109927","DOIUrl":"10.1016/j.compbiomed.2025.109927","url":null,"abstract":"<div><h3>Motivation</h3><div>Accurately predicting drug-target protein interactions (DTI) is a cornerstone of drug discovery, enabling the identification of potential therapeutic compounds. Sequence-based prediction models, despite their simplicity, hold great promise in extracting essential information directly from raw sequences. However, the focus in recent DTI studies has increasingly shifted toward enhancing algorithmic complexity, often at the expense of fully leveraging robust sequence representation learning methods. This shift has led to the underestimation and gradual neglect of methodologies aimed at effectively capturing discriminative features from sequences. Our work seeks to address this oversight by emphasizing the value of well-constructed sequence representation algorithms, demonstrating that even with simple interaction mapping algorithm techniques, accurate DTI models can be achieved. By prioritizing meaningful information extraction over excessive model complexity, we aim to advance the development of practical and generalizable DTI prediction frameworks.</div></div><div><h3>Results</h3><div>We developed the KNowledge Uniting DTI model (KNU-DTI), which retrieves structural information and unites them. Protein structural properties were obtained using structural property sequence (SPS). Extended-connectivity fingerprint (ECFP) was used to estimate the structure-activity relationship in molecules. Including these two features, a total of five latent vectors were derived from protein and molecule via various neural networks and integrated by elemental-wise addition to predict binding interactions or affinity. Using four test concepts to evaluate the model, we show that the model outperforms recently published competitors. Finally, a case study indicated that our model has a competitive edge over existing docking simulations in some cases.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"189 ","pages":"Article 109927"},"PeriodicalIF":7.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143520926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Association of Murray's law with atherosclerosis risk: Numerical validation of a general scaling law of arterial tree.

IF 7 2区医学

Computers in biology and medicine Pub Date : 2025-03-01 Epub Date: 2025-01-27 DOI: 10.1016/j.compbiomed.2025.109741

Mohammad Shumal, Mohsen Saghafian, Ebrahim Shirani, Mahdi Nili-AhmadAbadi

{"title":"Association of Murray's law with atherosclerosis risk: Numerical validation of a general scaling law of arterial tree.","authors":"Mohammad Shumal, Mohsen Saghafian, Ebrahim Shirani, Mahdi Nili-AhmadAbadi","doi":"10.1016/j.compbiomed.2025.109741","DOIUrl":"10.1016/j.compbiomed.2025.109741","url":null,"abstract":"<p><p>Atherogenesis is prone in medium and large-sized vessels, such as the aorta and coronary arteries, where hemodynamic stress is critical. Low and oscillatory wall shear stress contributes significantly to endothelial dysfunction and inflammation. Murray's law minimizes energy expenditure in vascular networks and applies to small arteries. However, its assumptions fail to account for the pulsatile nature of blood flow in larger, atherosclerosis-prone arteries. This study aims to numerically validate a novel general scaling law that extends Murray's law to incorporate pulsatile flow effects and demonstrate its applications in vascular health and artificial graft design. The proposed scaling law establishes an optimal relationship between arterial bifurcation characteristics and pulsatile flow dynamics, applicable throughout the vascular system. This work examines the relationship between deviations from Murray's law and the development of atherosclerosis in both coronary arteries and abdominal aorta bifurcations, explaining observed deviations from Murray's law in these regions. A finite volume method is applied to evaluate flow patterns in coronary arteries and aortoiliac bifurcations, incorporating in vivo pulsatile inflow and average outlet pressure. The results indicate that the proposed scaling law enhances wall shear stress distribution compared to Murray's law, which is characterized by higher wall shear stress and reduced oscillatory shear index. These findings suggest that vessels adhering to this scaling law are less susceptible to atherosclerosis. Furthermore, the results are consistent with clinical morphometric data, underscoring the potential of the proposed scaling law to optimize vascular graft designs, promoting favorable hemodynamic patterns and minimizing the occlusion risk in clinical applications.</p>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"186 ","pages":"109741"},"PeriodicalIF":7.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143058371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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