Critical reviews in biomedical engineering最新文献

The Safety and Efficacy of Cardiac Stem Cell Therapy for Cardiovascular Disease: A Meta-Analysis of Randomized Controlled Trials. 心脏干细胞治疗心血管疾病的安全性和有效性：随机对照试验的荟萃分析。

Critical reviews in biomedical engineering Pub Date : 2026-01-01 DOI: 10.1615/CritRevBiomedEng.2025059978

Fakher Rahim, Shamim Gozin

{"title":"The Safety and Efficacy of Cardiac Stem Cell Therapy for Cardiovascular Disease: A Meta-Analysis of Randomized Controlled Trials.","authors":"Fakher Rahim, Shamim Gozin","doi":"10.1615/CritRevBiomedEng.2025059978","DOIUrl":"10.1615/CritRevBiomedEng.2025059978","url":null,"abstract":"A multitude of studies have investigated the identification of unique antigens and genetic traits associated with cardiac stem cells (CSCs) since their discovery. This meta-analysis aims to assess the safety and efficacy of cardiac stem cells (CSCs), elucidate existing knowledge regarding their potential applications, and compare them with other novel therapeutic strategies for cardiac repair, including bone marrow cells (BMCs) and mesenchymal stem cells (MSCs). Researchers conducted a search of important indexing databases, including PubMed, Scopus, Cochrane Central, Web of Science (WOS), CINAHL, and Embase, to identify pertinent papers published from 1980 to January 2025. A total of 74 studies involving 5,420 participants were selected from 459 evaluated for the study. A total of 2,931 participants were allocated to the intervention group, whereas 2,489 were assigned to the placebo or control groups. The research encompassed 49 papers on BMC therapy, 17 on MSC therapy, five on CSC therapy, and three on ADRC therapy. A 0.4% enhancement in left ventricular ejection fraction (LVEF) [95% confidence interval (95% CI): 0.23-0.57; I2: 85%, P < 0.00001] was noted after stem cell therapy and in the stem cell therapy cohort, left ventricular end-systolic volume (LVESV) diminished by -0.33 mL (95% CI: -0.47 to -0.19; I2: 73%, P < 0.00001), whereas left ventricular end-diastolic volume (LVEDV) reduced by -0.18 mL (95% CI: -0.31 to -0.05; I2: 68%, P = 0.006). Furthermore, in this cohort, the six-minute walk test (6MWT) exhibited an increase of 0.2% (95% CI: 0.06-0.34; I2: 0%, P = 0.005), whereas the standardized mean difference of infarct size (IS) demonstrated a reduction of -0.36% (95% CI: -0.60 to -0.12; I2: 68%; P = 0.004). These findings augment the existing evidence and underscore the transformative potential of stem cell therapy in cardiac treatment.","PeriodicalId":94308,"journal":{"name":"Critical reviews in biomedical engineering","volume":"54 1","pages":"97-115"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147346196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Novel Investigation of Hepatitis B Transmission Dynamics via Fractal-Fractional Operators of Variable and Constant Order with Memory Effects. 基于记忆效应的变阶和常阶分形-分数阶算子的乙型肝炎传播动力学新研究。

Critical reviews in biomedical engineering Pub Date : 2026-01-01 DOI: 10.1615/CritRevBiomedEng.2025059960

Sumit Gupta, Pawan Kumar Jain, Deepika Khandelwal

引用次数: 0

Diffusion Tensor Imaging for Brain Injury Assessment: Methodological Foundations and Clinical Insights. 脑损伤评估的弥散张量成像：方法学基础和临床见解。

Critical reviews in biomedical engineering Pub Date : 2026-01-01 DOI: 10.1615/CritRevBiomedEng.2025059839

Nicholas Simard, Michael D Noseworthy

{"title":"Diffusion Tensor Imaging for Brain Injury Assessment: Methodological Foundations and Clinical Insights.","authors":"Nicholas Simard, Michael D Noseworthy","doi":"10.1615/CritRevBiomedEng.2025059839","DOIUrl":"10.1615/CritRevBiomedEng.2025059839","url":null,"abstract":"Diffusion tensor imaging (DTI) has emerged as a powerful neuroimaging modality for investigating white matter microstructure and its alterations following brain injury. This review presents a comprehensive overview of DTI, encompassing its physical principles, mathematical modeling of diffusion tensors, and known limitations of the technique. We explore key methodological considerations, including acquisition protocols, preprocessing pipelines, vendor-related variability, atlas registration, and the role of diffusion phantoms in calibration. With the rise of big data in medical imaging, we highlight the influence of large-scale, multisite datasets and open-source neuroimaging repositories in advancing DTI research. A central focus is placed on the application of DTI in mild traumatic brain injury, a condition that often eludes detection in conventional imaging settings. We evaluate emerging computational strategies, including Z-score analysis, principal component analysis, random forests, and generative adversarial networks-that improve the sensitivity, specificity, and interpretability of DTI metrics in both clinical and research settings. By bridging methodological rigor with translational insight, this review underscores the evolving potential of DTI as a neuroimaging biomarker for brain injury assessment.","PeriodicalId":94308,"journal":{"name":"Critical reviews in biomedical engineering","volume":"54 1","pages":"49-66"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147346192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Improved YOLOv8-Based Object Detection Algorithm for Skin Diseases. 一种改进的基于yolov8的皮肤病目标检测算法

Critical reviews in biomedical engineering Pub Date : 2026-01-01 DOI: 10.1615/CritRevBiomedEng.2025059866

Xinglong Yu

{"title":"An Improved YOLOv8-Based Object Detection Algorithm for Skin Diseases.","authors":"Xinglong Yu","doi":"10.1615/CritRevBiomedEng.2025059866","DOIUrl":"10.1615/CritRevBiomedEng.2025059866","url":null,"abstract":"Accurate and effective diagnosis of skin diseases is crucial for clinical decision-making. However, there are still some challenges, including irregular lesion morphologies, class imbalance between rare and common types, and performance degradation in complex scenarios characterized by noise or occlusion. To address these issues, an improved skin disease detection algorithm is proposed based on YOLOv8n, which features three core innovations. First, it integrates deformable large kernel attention (D-LKA) into deep backbone layers to capture global contextual relationships of lesions; then it embeds DCNv3 deformable convolutions in mid-layers to adaptively sample irregular lesion boundaries; finally, it designs an EMA-Slide Loss function to dynamically weight hard-to-classify samples, thereby reducing bias toward common categories. After evaluating on the International Skin Imaging Collaboration (ISIC) dataset (with labels validated by board-certified dermatologists), the algorithm can achieve 96.58% mAP50 and 88.32% mAP50-95, 2.44% and 2.52% higher than the baseline YOLOv8n, respectively. It maintains a real-time inference speed of 31 ms per image, making it suitable for edge devices such as portable dermatoscopes. Supporting nine common types of skin diseases, with extensibility to accommodate rare types and multi-modal data fusion, this work provides a clinically actionable tool for automated skin lesion analysis, bridging the gap between algorithmic performance and real-world clinical demands.","PeriodicalId":94308,"journal":{"name":"Critical reviews in biomedical engineering","volume":"54 1","pages":"1-16"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147346204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Local-Global-Graph Network-Based Biokey Generation with Electrocardiogram Signal and Lightweight Authentication in Cloud-Based Internet of Medical Things Networks. 基于局部-全局图网络的心电图信号生物密钥生成与云医疗物联网轻量化认证。

Critical reviews in biomedical engineering Pub Date : 2026-01-01 DOI: 10.1615/CritRevBiomedEng.2025058925

Sanjeev Kumar Adhinki Nagarathinam, Ramesh Naik Bhukya

{"title":"Local-Global-Graph Network-Based Biokey Generation with Electrocardiogram Signal and Lightweight Authentication in Cloud-Based Internet of Medical Things Networks.","authors":"Sanjeev Kumar Adhinki Nagarathinam, Ramesh Naik Bhukya","doi":"10.1615/CritRevBiomedEng.2025058925","DOIUrl":"10.1615/CritRevBiomedEng.2025058925","url":null,"abstract":"The internet of medical things (IoMT) is regarded as a promising framework, which is used to expand and improve telemedicine services. Cloud-based IoMT refers to the integration of medical devices and sensors with cloud computing infrastructure, enabling real-time remote data collection, processing, storage, and analysis. This architecture supports the efficient management of patient health information and facilitates advanced telemedicine services by offering scalable, secure, and accessible healthcare solutions. Ensuring secure access and communication in such systems is critical, as vulnerabilities in the network can expose sensitive patient data to significant risks. Among various security measures, authentication using biomedical signals, particularly electrocardiogram (ECG) signals, is gaining attention due to their unique, individual-specific characteristics. Therefore, this paper develops a new approach called local-global-graph network-based biokey generation (LGGNet-BioKey) for authentication in Cloud-based IoMT. Initially, the Cloud-based IoMT network is simulated, and it includes three entities, like cloud server, gateway, and patient. First, the public key and security parameters are initialized, and then the entities are registered with the cloud server. Next, the key generation is done using LGGNet, and then the BioKey generation is performed using an ECG signal. Next, the lightweight authentication is done and lastly, attribute-based encryption and decryption are performed in the data preservation phase. Furthermore, the LGGNet-BioKey model measured an execution time, memory usage, and key generation time of 3.772 sec, 9.096 MB, and 3.771 sec.","PeriodicalId":94308,"journal":{"name":"Critical reviews in biomedical engineering","volume":"54 1","pages":"67-95"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147346219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mathematical Probe of Nanoparticle Aggregation in Capillary-Tissue System Applying Fractal Model. 应用分形模型对纳米颗粒在毛细管-组织系统中聚集的数学探讨。

Critical reviews in biomedical engineering Pub Date : 2025-01-01 DOI: 10.1615/CritRevBiomedEng.2024055532

Bhawini Prasad

引用次数: 0

The Burn Grafting Image Reclamation Redefined with the Peak-Valley Approach. 用峰谷法重新定义烧伤嫁接图像复原。

Critical reviews in biomedical engineering Pub Date : 2025-01-01 DOI: 10.1615/CritRevBiomedEng.v53.i2.40

B P Pradeep Kumar, E Naresh, A Ashwitha, Kadiri Thirupal Reddy, N N Srinidhi

{"title":"The Burn Grafting Image Reclamation Redefined with the Peak-Valley Approach.","authors":"B P Pradeep Kumar, E Naresh, A Ashwitha, Kadiri Thirupal Reddy, N N Srinidhi","doi":"10.1615/CritRevBiomedEng.v53.i2.40","DOIUrl":"https://doi.org/10.1615/CritRevBiomedEng.v53.i2.40","url":null,"abstract":"Burn injuries constitute a significant public health challenge, often necessitating the expertise of medical professionals for diagnosis. However, in scenarios where specialized facilities are unavailable, the utility of automated burn assessment tools becomes evident. Factors such as burn area, depth, and location play a pivotal role in determining burn severity. In this study, we present a classification model for burn diagnosis, leveraging automated machine learning techniques. Our approach includes an image reclamation system that incorporates the peak and valley algorithm, ensuring the removal of noise while consistently delivering high-quality results. By using skewness and kurtosis, we demonstrate substantial improvements in diagnostic accuracy. Our proposed system sources key features from enhanced grafting samples using peak valley transformation, enabling the computation of BQs and a unique bin analysis to enhance image reclamation. Our experimental results highlight efficiency gains, notably growing the matching features of graft samples for 14 matching images. The intended work involves the creation of a burn classification reclamation model. The proposed approach utilizes a support vector machine (SVM). The evaluation of the model will be conducted using an untrained catalogue, with a specific focus on its effectiveness in reclaiming images that necessitate grafts and distinguishing them from those that do not. Our approach holds promise in grafting sample reclamation in emergency settings, thereby expediting more accurate diagnoses and treatments for acute burn injuries. This work has the latent to save lives and improve patient upshots in burn traumas.","PeriodicalId":94308,"journal":{"name":"Critical reviews in biomedical engineering","volume":"53 2","pages":"21-35"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144762942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Nonlinear Dynamics and Stability Analysis of a Pandemic Model Using Homotopy Perturbation. 基于同伦摄动的流行病模型的非线性动力学与稳定性分析。

Critical reviews in biomedical engineering Pub Date : 2025-01-01 DOI: 10.1615/CritRevBiomedEng.2025055055

Garima Agarwal, Man Mohan Singh, Rashid Jan, Sunil Dutt Purohit

引用次数: 0

Editorial Preface: Mathematical Biology. 编辑前言：数学生物学。

Critical reviews in biomedical engineering Pub Date : 2025-01-01 DOI: 10.1615/CritRevBiomedEng.v53.i3.10

Dharmendra Tripathi, Kalpana Sharma, Rajashekhar Choudhari, Rajesh K Pandey, Sreedhara Rao Gunakala

引用次数: 0

A New Approach to Population Growth Model Involving a Logistic Differential Equation of Fractional Order. 涉及分数阶Logistic微分方程的人口增长模型的新方法。

Critical reviews in biomedical engineering Pub Date : 2025-01-01 DOI: 10.1615/CritRevBiomedEng.2024055114

Deepika Jain, Alok Bhargava, Sumit Gupta

{"title":"A New Approach to Population Growth Model Involving a Logistic Differential Equation of Fractional Order.","authors":"Deepika Jain, Alok Bhargava, Sumit Gupta","doi":"10.1615/CritRevBiomedEng.2024055114","DOIUrl":"10.1615/CritRevBiomedEng.2024055114","url":null,"abstract":"Population growth and its consequences remain one of the most pressing challenges of our time. The study of population dynamics, including factors like resource availability, disease, and environmental constraints, is fundamental for planning in various domains such as ecology, economics, and public health. One of the earliest models proposed to explain population growth was by Thomas Robert Malthus in the late 18th century. Malthus theorized that populations grow exponentially, while the food supply increases only in an arithmetic manner and that was explained by a mathematical model i.e. the population growth model. This imbalance, according to Malthus, could eventually lead to resource scarcity and population collapse. However, Malthus's model, though foundational, was simplistic in nature. Over time, a more refined and realistic model was developed by Pierre François Verhulst, a Belgian mathematician, which led to the formulation of the logistic growth model. This model involves a fractional differential equation (FDE) namely the logistic differential equation. Due to the significance of FDEs, several authors have proposed solutions for the model using different techniques. Our work finds this model's solution using the Laplace decomposition method (LDM) approach. The method represents a significant advancement in the tool case of applied mathematicians and scientists. Its ability to efficiently and accurately solve complex differential equations, especially FPDEs. The graphical interpretation of the behavior of the result is also mentioned and compare our results with exact solutions found in literature.","PeriodicalId":94308,"journal":{"name":"Critical reviews in biomedical engineering","volume":"53 2","pages":"37-48"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144762938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0