Computers in biology and medicine最新文献

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Dynamic topographies of intrinsic neural timescales: a key role for consciousness 内在神经时间尺度的动态地形:意识的关键作用。
IF 6.3 2区 医学
Computers in biology and medicine Pub Date : 2025-09-22 DOI: 10.1016/j.compbiomed.2025.111102
Andrea Buccellato , Di Zang , Yasir Çatal , Bianca Ventura , Massimiliano Facca , Zengxin Qi , Patrizia Bisiacchi , Alessandra Del Felice , Xuehai Wu , Georg Northoff
{"title":"Dynamic topographies of intrinsic neural timescales: a key role for consciousness","authors":"Andrea Buccellato ,&nbsp;Di Zang ,&nbsp;Yasir Çatal ,&nbsp;Bianca Ventura ,&nbsp;Massimiliano Facca ,&nbsp;Zengxin Qi ,&nbsp;Patrizia Bisiacchi ,&nbsp;Alessandra Del Felice ,&nbsp;Xuehai Wu ,&nbsp;Georg Northoff","doi":"10.1016/j.compbiomed.2025.111102","DOIUrl":"10.1016/j.compbiomed.2025.111102","url":null,"abstract":"<div><div>The brain displays intrinsic durations in its own spontaneous activity - Intrinsic Neural Timescales (INTs). INTs are hierarchically organized, with shorter durations within unimodal regions and longer intervals in multimodal domains. Despite significant progress, it's currently not known whether the unimodal-multimodal hierarchical organization undergoes recurrent changes itself - consistent with the existence of a dynamic repertoire of INT topographies. To this aim, we characterized the dynamics of topographic INT states by clustering the dynamic ACW-0 matrices in two different datasets: the source-reconstructed HCP resting-state MEG dataset, and a hd-EEG resting-state dataset, composed of healthy individuals and people with disorders of consciousness (DoCs). We found that healthy subjects display dynamic transitions between different INT states, which exhibit changing degrees of uni-transmodal cortical hierarchies. These dynamic transitions show non-random behavior, with moderate degrees of unpredictability and evidence of nontrivial memory effects. Unlike in healthy subjects, these properties are disrupted in DoC patients, who exhibit less predictable INT state transitions and less memory effects. Together, our results show a prominent role for the temporal richness of the transitions between different INT topographic states in the awake state which, as evidenced by our results, is key for maintaining an adequate level of consciousness.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"197 ","pages":"Article 111102"},"PeriodicalIF":6.3,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145112225","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
Strategic frameworks: A review of game theory methods for privacy preservation in digital health 战略框架:数字健康中隐私保护的博弈论方法综述
IF 6.3 2区 医学
Computers in biology and medicine Pub Date : 2025-09-22 DOI: 10.1016/j.compbiomed.2025.111124
Hamed Narimani , Maryam Ansarian , Zahra Baharlouei
{"title":"Strategic frameworks: A review of game theory methods for privacy preservation in digital health","authors":"Hamed Narimani ,&nbsp;Maryam Ansarian ,&nbsp;Zahra Baharlouei","doi":"10.1016/j.compbiomed.2025.111124","DOIUrl":"10.1016/j.compbiomed.2025.111124","url":null,"abstract":"<div><div>With the advancement of technology and the transition towards a digital world, the field of health and medicine is rapidly evolving in this direction. To fully harness the benefits of digital health, it is crucial to address the associated challenges. Given the necessity of exchanging personal information between patients and healthcare centers over communication networks, ensuring security and preserving privacy are important challenging issues in this field. Various approaches have been proposed in the literature to tackle these challenges. Some studies have utilized game theory to analyze and model the issues of security and privacy. Over recent decades, game theory has proven its versatility in modeling and solving a variety of problems. Research indicates that game theory can significantly enhance healthcare outcomes, having been utilized across numerous specialties such as disease diagnosis, public health, cancer treatment, medical consultations, clinical decision-making, privacy, and security of medical information. In this paper, for the first time, we review game-theory-based methods for preserving privacy and security in digital health, categorizing them based on the types of games modeled. Our study results show that the most commonly used game models in this field are, in order, the Stackelberg, the Strategic, and the Evolutionary games. Based on the research conducted in each category of games, we extract the common model used so that these models can be utilized in future research.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"197 ","pages":"Article 111124"},"PeriodicalIF":6.3,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118160","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
Developing federated time-to-event scores using heterogeneous real-world survival data 使用异构的真实生存数据开发联邦时间到事件评分。
IF 6.3 2区 医学
Computers in biology and medicine Pub Date : 2025-09-22 DOI: 10.1016/j.compbiomed.2025.111084
Siqi Li , Ziwen Wang , Yuqing Shang , Qiming Wu , Chuan Hong , Yilin Ning , Di Miao , Marcus Eng Hock Ong , Bibhas Chakraborty , Nan Liu
{"title":"Developing federated time-to-event scores using heterogeneous real-world survival data","authors":"Siqi Li ,&nbsp;Ziwen Wang ,&nbsp;Yuqing Shang ,&nbsp;Qiming Wu ,&nbsp;Chuan Hong ,&nbsp;Yilin Ning ,&nbsp;Di Miao ,&nbsp;Marcus Eng Hock Ong ,&nbsp;Bibhas Chakraborty ,&nbsp;Nan Liu","doi":"10.1016/j.compbiomed.2025.111084","DOIUrl":"10.1016/j.compbiomed.2025.111084","url":null,"abstract":"<div><h3>Objective</h3><div>Survival analysis serves as a fundamental component in numerous healthcare applications, where the determination of the time to specific events (such as the onset of a certain disease or death) for patients is crucial for clinical decision-making. Scoring systems are widely used for swift and efficient risk prediction. However, existing methods for constructing survival scores presume that data originates from a single source, posing privacy challenges in collaborations with multiple data owners.</div></div><div><h3>Materials and methods</h3><div>We propose a novel framework for building federated scoring systems for multi-site survival outcomes, ensuring both privacy and communication efficiency. We applied our approach to sites with heterogeneous survival data originating from emergency departments in Singapore and the United States. Additionally, we independently developed local scores at each site.</div></div><div><h3>Results</h3><div>In testing datasets from each participant site, our proposed federated scoring system consistently outperformed all local models, evidenced by higher integrated area under the receiver operating characteristic curve (iAUC) values, with a maximum improvement of 11.6 %. Additionally, the federated score's time-dependent AUC(t) values showed advantages over local scores, exhibiting narrower confidence intervals (CIs) across most time points.</div></div><div><h3>Discussion</h3><div>The model developed through our proposed method showed good local performance and is promising for future healthcare research. Sites participating in our proposed federated scoring model training can develop survival models with enhanced prediction accuracy and efficiency.</div></div><div><h3>Conclusion</h3><div>This study demonstrates the effectiveness of our privacy-preserving federated survival score generation framework and its applicability to real-world heterogeneous survival data.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"197 ","pages":"Article 111084"},"PeriodicalIF":6.3,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145112195","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
Benign vs malignant tumors classification from tumor outlines in mammography scans using artificial intelligence techniques 利用人工智能技术从乳房x线摄影扫描中的肿瘤轮廓分类良性与恶性肿瘤
IF 6.3 2区 医学
Computers in biology and medicine Pub Date : 2025-09-22 DOI: 10.1016/j.compbiomed.2025.111118
Hamidreza Mortazavy Beni, Fatemeh Yekta Asaei
{"title":"Benign vs malignant tumors classification from tumor outlines in mammography scans using artificial intelligence techniques","authors":"Hamidreza Mortazavy Beni,&nbsp;Fatemeh Yekta Asaei","doi":"10.1016/j.compbiomed.2025.111118","DOIUrl":"10.1016/j.compbiomed.2025.111118","url":null,"abstract":"<div><div>Breast cancer is one of the most important causes of death among women due to cancer. With the early diagnosis of this condition, the probability of survival will increase. For this purpose, medical imaging methods, especially mammography, are used for screening and early diagnosis of breast abnormalities. The main goal of this study is to distinguish benign or malignant tumors based on tumor morphology features extracted from tumor outlines extracted from mammography images. Unlike previous studies, this study does not use the mammographic image itself but only extracts the exact outline of the tumor.</div><div>These outlines were extracted from a new and publicly available mammography database published in 2024. The features outlines were calculated using known pre-trained Convolutional Neural Networks (CNN), including VGG16, ResNet50, Xception65, AlexNet, DenseNet, GoogLeNet, Inception-v3, and a combination of them to improve performance. These pre-trained networks have been used in many studies in various fields. In the classification part, known Machine Learning (ML) algorithms, such as Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Neural Network (NN), Naïve Bayes (NB), Decision Tree (DT), and a combination of them have been compared in outcome measures, namely accuracy, specificity, sensitivity, and precision. Also, with the use of data augmentation, the dataset size was increased about 6–8 times, and the K-fold cross-validation technique (K = 5) was used in this study. Based on the performed simulations, a combination of the features from all pre-trained deep networks and the NB classifier resulted in the best possible outcomes with 88.13 % accuracy, 92.52 % specificity, 83.73 % sensitivity, and 92.04 % precision. Furthermore, validation on DMID dataset using ResNet50 features along with NB classifier, led to 92.03 % accuracy, 95.57 % specificity, 88.49 % sensitivity, and 95.23 % precision. This study sheds light on using AI algorithms to prevent biopsy tests and speed up breast cancer tumor classification using tumor outlines in mammographic images.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"197 ","pages":"Article 111118"},"PeriodicalIF":6.3,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118158","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
Machine learning–driven discovery of NSC828779 as a multi-mechanistic NLRP3 inflammasome inhibitor for inflammatory diseases 机器学习驱动的NSC828779作为炎性疾病多机制NLRP3炎性体抑制剂的发现
IF 6.3 2区 医学
Computers in biology and medicine Pub Date : 2025-09-22 DOI: 10.1016/j.compbiomed.2025.111110
Sung-Ling Tang , Maryam Rachmawati Sumitra , Lung-Ching Chen , Feng-Cheng Liu , Han-Lin Hsu , Yu-Cheng Kuo , Muhamad Ansar , Sheng-Liang Huang , Shih-Yu Lee , Hong-Jaan Wang , Bashir Lawal , Alexander T.H. Wu , Ya-Ting Wen , Hsu-Shan Huang
{"title":"Machine learning–driven discovery of NSC828779 as a multi-mechanistic NLRP3 inflammasome inhibitor for inflammatory diseases","authors":"Sung-Ling Tang ,&nbsp;Maryam Rachmawati Sumitra ,&nbsp;Lung-Ching Chen ,&nbsp;Feng-Cheng Liu ,&nbsp;Han-Lin Hsu ,&nbsp;Yu-Cheng Kuo ,&nbsp;Muhamad Ansar ,&nbsp;Sheng-Liang Huang ,&nbsp;Shih-Yu Lee ,&nbsp;Hong-Jaan Wang ,&nbsp;Bashir Lawal ,&nbsp;Alexander T.H. Wu ,&nbsp;Ya-Ting Wen ,&nbsp;Hsu-Shan Huang","doi":"10.1016/j.compbiomed.2025.111110","DOIUrl":"10.1016/j.compbiomed.2025.111110","url":null,"abstract":"<div><div>The NLRP3 inflammasome is a key regulator of the innate immune response and a promising therapeutic target in inflammation-driven diseases. This study aimed to identify potent nature inspired small molecules using AI-guided in silico techniques integrated with NCI-60 high-throughput assays. We developed a machine learning–driven platform that combines pharmacophore modeling, molecular docking, MDS, and RNNs to prioritize candidate compounds. Among these, NSC828779 emerged as a lead scaffold, demonstrating high binding affinity to the ATP-binding site of NLRP3 and superior interaction energy and stability compared to known inhibitors. Docking scores were strongest for NLRP3 (−10.5 kcal/mol), caspase-1 (−8.6 kcal/mol), and ASC (−8.5 kcal/mol), outperforming MCC950, glyburide, and other reference compounds. MDS confirmed the stability of the NLRP3–ASC–caspase-1 complex, supported by RMSD and RMSF analyses showing enhanced conformational integrity. ADMET profiling predicted favorable drug-likeness, solubility, moderate lipophilicity, and low toxicity. Mechanistically, NSC828779 may act as a multi-mechanistic NLRP3 inhibitor by disrupting protein–protein interactions, inhibiting NF-κB signaling, and inducing autophagy. These results establish NSC828779 as a promising candidate for treating inflammation-related disorders and underscore the utility of AI-driven drug discovery platforms in identifying novel inflammasome-targeted therapeutics. Further in vitro and in vivo validation is warranted to support its clinical development.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"197 ","pages":"Article 111110"},"PeriodicalIF":6.3,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118159","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
Automatic motor and visuospatial cognition screening with ensemble learning: A computerised clock drawing test approach 集成学习的自动运动和视觉空间认知筛选:计算机化时钟绘图测试方法
IF 6.3 2区 医学
Computers in biology and medicine Pub Date : 2025-09-20 DOI: 10.1016/j.compbiomed.2025.111107
Andrius Lauraitis, Armantas Ostreika, Gintaras Palubeckis, Liudas Motiejunas
{"title":"Automatic motor and visuospatial cognition screening with ensemble learning: A computerised clock drawing test approach","authors":"Andrius Lauraitis,&nbsp;Armantas Ostreika,&nbsp;Gintaras Palubeckis,&nbsp;Liudas Motiejunas","doi":"10.1016/j.compbiomed.2025.111107","DOIUrl":"10.1016/j.compbiomed.2025.111107","url":null,"abstract":"&lt;div&gt;&lt;div&gt;We propose a supervised ensemble learning-based approach to evaluate the significance of the digitised analogue clock drawing test (CDT) for the detection of neural impairments in patients with early-stage central nervous system disorders (CNSD). The research findings are based on the data samples that have been collected using the clock construction task of the Neural Impairment Test Suite (NITS) mobile application from 15 test subjects (including Huntington Disease (HD), Parkinson Disease (PD), cerebral palsy (CP), post-stroke, early dementia and control groups) during a pilot study in Lithuania. This work examines finger motion tracking (FMT) on a mobile device and the detection of potential inability of CNSD patients to accurately copy benchmark clock drawings without a pre-drawn clock contour circle, focusing on multimodal (datasets of FMT samples and CDT images) neural impairment screening. Considering the small size of the originally gathered imbalanced datasets, as pre-processing routines, Synthetic Minority Oversampling Technique (SMOTE) was used for the FMT augmentation, and the geometric image transformations (rotation, flip, zoom) were applied for the augmentation of CDT drawings.&lt;/div&gt;&lt;div&gt;The following methods for feature extraction are used regarding the FMT and CDT image datasets accordingly: 1) average finger speed while moving on the surface, finger velocity, magnitude of the rate at which finger tap changes its position, standard deviation (SD) of velocity, rate at which finger velocity changes, maximum finger acceleration, finger position change count, average finger screen pressure and touch area ratio (in range [0; 1]), total time duration (in seconds); 2) Edge Histogram Filter (EHD), Pyramid Histogram of Oriented Gradients (PHOG), Gabor wavelet and their fusion.&lt;/div&gt;&lt;div&gt;Two experiments (E1, E2) were conducted to solve healthy vs. impaired binary classification problem. The nature of E1 design that is tracking motor impairments in CNSD and detecting cognitive impairments is targeted in E2. All classifiers (K-NN, Naïve Bayes, ANN, SMO, SVM and their ensembles) were tested with a 5-fold stratified cross-validation procedure, and the performances of classification models were evaluated by accuracy, balanced accuracy (BA), F1 score, sensitivity, specificity, kappa, receiver-operating characteristic area under the curve (AUC-ROC), mean absolute error (MAE), root mean squared error (RMSE) metrics. The Principal Component Analysis (PCA) method was used for the dimensionality reduction in high-dimensional image feature vectors. The overfitting of models was addressed by comparing the learning curves (training and validation sets). Results: 1) in E1, the highest 99.20 % accuracy precision (boosted SMO algorithm with PuK kernel) was achieved on SMOTE synthesised FMT train set and 99.40 % accuracy on FMT test set; 2) in E2 (augmented dataset of CDT images), the highest 97.96 % accuracy (94.90 % on test set) was achieved wit","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"197 ","pages":"Article 111107"},"PeriodicalIF":6.3,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099573","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
Antioxidant efficacy of hydroxytyrosol, tyrosol, homovanillic alcohol, and their acetate derivatives in Parkinson's disease: A synergistic computational approach 羟基酪醇、酪醇、同型香草醇及其乙酸酯衍生物在帕金森病中的抗氧化功效:一种协同计算方法
IF 6.3 2区 医学
Computers in biology and medicine Pub Date : 2025-09-20 DOI: 10.1016/j.compbiomed.2025.111104
Rituraj Barman , Benzir Ahmed , Hemchandra Deka , Manazira Ahmed , Pratyashee Barukial , Debabrat Baishya , Bipul Bezbaruah
{"title":"Antioxidant efficacy of hydroxytyrosol, tyrosol, homovanillic alcohol, and their acetate derivatives in Parkinson's disease: A synergistic computational approach","authors":"Rituraj Barman ,&nbsp;Benzir Ahmed ,&nbsp;Hemchandra Deka ,&nbsp;Manazira Ahmed ,&nbsp;Pratyashee Barukial ,&nbsp;Debabrat Baishya ,&nbsp;Bipul Bezbaruah","doi":"10.1016/j.compbiomed.2025.111104","DOIUrl":"10.1016/j.compbiomed.2025.111104","url":null,"abstract":"<div><div>Phenolic plant metabolites, including hydroxytyrosol, tyrosol, homovanillic alcohol, and their acetate derivatives, have emerged as potent antioxidants and promising therapeutic candidates for neurodegenerative disorders. These compounds exhibit dual functionality by efficiently scavenging reactive free radicals and targeting key protein residues, thereby alleviating oxidative stress and preventing cellular damage. Using multiscale <em>in silico</em> methodologies, their interactions with peroxyl (ROO<sup>•</sup>) and hydroperoxyl (HOO<sup>•</sup>) radicals, as well as with Monoamine Oxidase A (MAO-A), a pivotal enzyme in Parkinson's disease, were systematically investigated. Density Functional Theory (DFT) analyses illustrate radical stabilization pathways, supported by MEP, SD, NBO, FMO, and Fukui function descriptors. Hirshfeld surface analysis (HSA) and QTAIM further reveal strong binding hotspots, predominantly stabilized by conventional hydrogen bonding complemented with hydrophobic non-covalent contacts. ADMET profiling underscored favorable pharmacokinetic properties and drug-likeness. Finally, molecular docking and molecular dynamics (MD) simulations confirmed their stable accommodation within the MAO-A catalytic pocket, highlighting significant binding affinities and critical interacting residues. Overall, these findings establish hydroxytyrosol, tyrosol and homovanillic alcohol derivatives as potential multifunctional neuroprotective agents against Parkinson's disease.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"197 ","pages":"Article 111104"},"PeriodicalIF":6.3,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099575","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
Effects of pulmonary hypertension on right ventricular mechanics and coronary perfusion: Insights from computational simulations 肺动脉高压对右心室力学和冠状动脉灌注的影响:来自计算模拟的见解
IF 6.3 2区 医学
Computers in biology and medicine Pub Date : 2025-09-20 DOI: 10.1016/j.compbiomed.2025.111113
Chenghan Cai , Jenny S. Choy , Ge He , Michael E. Widlansky , Ghassan S. Kassab , Lei Fan
{"title":"Effects of pulmonary hypertension on right ventricular mechanics and coronary perfusion: Insights from computational simulations","authors":"Chenghan Cai ,&nbsp;Jenny S. Choy ,&nbsp;Ge He ,&nbsp;Michael E. Widlansky ,&nbsp;Ghassan S. Kassab ,&nbsp;Lei Fan","doi":"10.1016/j.compbiomed.2025.111113","DOIUrl":"10.1016/j.compbiomed.2025.111113","url":null,"abstract":"<div><div>Pulmonary hypertension (PH), defined by elevated mean pulmonary arterial pressure (mPAP), is a leading cause of right heart failure (RHF). However, the mechanisms linking PH to ventricular dysfunction and coronary ischemia remain unclear. An advanced mechanistic understanding is critical for improving clinical diagnosis and treatment strategies. This study aimed to investigate the impact of acute and chronic PH on biventricular mechanics and coronary perfusion. We developed a computational model that integrates coronary perfusion in the major coronary arteries with a biventricular finite element (FE) model in a closed-loop systemic and pulmonary circulation. Validated against clinical measurements, the computational model was applied to simulate the hemodynamics and myocardial perfusion across coronary territories and myocardial walls under conditions of acute and chronic PH. Model predictions demonstrated that in acute PH, coronary flow in the right ventricular free wall (RVFW) and septum was reduced due to elevated intramyocardial pressure (IMP), especially in the endocardium. In chronic PH, coronary flow was reduced in the RVFW, septum, and left ventricular free wall (LVFW) due to diminished perfusion pressure. These findings are consistent with clinical observations: the right-dominant right coronary artery (RCA) is more vulnerable to ischemia in acute PH, whereas the left-dominant left circumflex artery (LCx) is more vulnerable in chronic PH. In conclusion, chronic PH may contribute to subclinical left ventricular dysfunction and increased ischemic risk through impaired coronary perfusion, highlighting potential targets for therapeutic interventions in PH-related RHF.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"197 ","pages":"Article 111113"},"PeriodicalIF":6.3,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099576","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
Few-shot diagnosis of chest x-ray images using auxiliary information guided semi-deterministic infinite mixture prototypes 辅助信息引导的半确定性无限混合原型胸片少射诊断
IF 6.3 2区 医学
Computers in biology and medicine Pub Date : 2025-09-20 DOI: 10.1016/j.compbiomed.2025.111053
Prabhala Sandhya Gayatri , Devi Prasad Maharathy , Angshuman Paul
{"title":"Few-shot diagnosis of chest x-ray images using auxiliary information guided semi-deterministic infinite mixture prototypes","authors":"Prabhala Sandhya Gayatri ,&nbsp;Devi Prasad Maharathy ,&nbsp;Angshuman Paul","doi":"10.1016/j.compbiomed.2025.111053","DOIUrl":"10.1016/j.compbiomed.2025.111053","url":null,"abstract":"<div><div>We propose a few-shot learning (FSL) approach for the diagnosis of chest x-ray images. Our model can be trained with a small number of annotated data by utilizing auxiliary semantic information about the abnormalities under consideration. In our design, we consider the fact that because of various factors, there may be variations in the visual characteristics of an abnormality in x-rays. Hence, in a multi-label dataset, it is challenging to represent data points with a particular abnormality in one cluster based on visual features. Our few-shot learning approach dynamically generates multiple clusters to accurately represent a particular abnormality. The generation of multiple clusters is achieved using a semi-deterministic infinite mixture prototype method. The clustering process is guided by semantic information corresponding to the abnormalities. Thus, our method aims to create a discriminative representation for x-ray images utilizing semantic information about the abnormalities under consideration. Experiments on publicly available chest x-ray datasets show the efficacy of the proposed method for the diagnosis of chest x-ray images. Our code is publicly available in this <span><span>repository</span><svg><path></path></svg></span>.<span><span><sup>2</sup></span></span></div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"197 ","pages":"Article 111053"},"PeriodicalIF":6.3,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099574","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
Enhancing the reliability of Alzheimer's disease prediction in MRI images 增强阿尔茨海默病MRI图像预测的可靠性
IF 6.3 2区 医学
Computers in biology and medicine Pub Date : 2025-09-19 DOI: 10.1016/j.compbiomed.2025.111111
Junaidul Islam , Elvin Nur Furqon , Isack Farady , John Sahaya Rani Alex , Cheng-Ting Shih , Chia-Chen Kuo , Chih-Yang Lin
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