Computers in biology and medicine最新文献

Corrigendum to "Omicron variant receptor-binding domain phylogenetics and molecular dynamics" [Comput. Biol. Med. 146, (2022), 105633]. “组粒变异受体结合域系统发育和分子动力学”的勘误表[计算机]。医学杂志。医学杂志，（2022），105633。

IF 6.3 2区医学

Computers in biology and medicine Pub Date : 2026-10-16 DOI: 10.1016/j.compbiomed.2026.111987

Mahmoud Kandeel, Wael El-Deeb

引用次数: 0

Retraction notice to "Based on the Cancer Genome Atlas Database Development of a prognostic model of RNA binding protein in stomach adenocarcinoma" [Computers in Biology and Medicine 164 (2023) 107307] “基于肿瘤基因组图谱数据库构建胃腺癌RNA结合蛋白预后模型”的撤回通知[生物与医学计算机164(2023)107307]。

IF 6.3 2区医学

Computers in biology and medicine Pub Date : 2026-10-15 Epub Date: 2026-10-05 DOI: 10.1016/j.compbiomed.2026.111966

Sayed Haidar Abbas Raza, Ruimin Zhong, Shen Xing, Xiaoting Yu, Liang Chengcheng, Linsen Zan, Nicola M. Schreurs, Sameer D. Pant, Hongtao Lei

引用次数: 0

Corrigendum to “Poisson-based image editing for semi-supervised vitiligo lesion segmentation with limited annotations” [Comput. Biol. Med. 165, (2023), 107320] “基于泊松的半监督白癜风病变分割的有限注释图像编辑”的勘误表[计算机]。医学杂志。医学杂志，（2023），107 [j]。

IF 6.3 2区医学

Computers in biology and medicine Pub Date : 2026-10-15 Epub Date: 2026-10-10 DOI: 10.1016/j.compbiomed.2026.111984

Jiacong Wang, Xiaolan Ding, Jun Xiao

引用次数: 0

Retraction notice to "A new weakly supervised deep neural network for recognizing Alzheimer's disease" [Computers in Biology and Medicine 163 (2023) 107079]. “一种新的弱监督深度神经网络用于阿尔茨海默病的识别”[生物与医学计算机163(2023)107079]。

IF 6.3 2区医学

Computers in biology and medicine Pub Date : 2026-10-15 DOI: 10.1016/j.compbiomed.2026.111991

Xiaobo Zhang, Zhimin Li, Qian Zhang, Zegang Yin, Zhijie Lu, Yang Li

引用次数: 0

Retraction notice to "ViTU-net: A hybrid deep learning model with patch-based LSB approach for medical image watermarking and authentication using a hybrid metaheuristic algorithm" [Computers in Biology and Medicine 194 (2025) 110393] 对“ViTU-net：一种基于补丁的LSB方法的混合深度学习模型，用于医学图像水印和使用混合元启发式算法的认证”的撤回通知[生物与医学计算机194(2025)110393]。

IF 6.3 2区医学

Computers in biology and medicine Pub Date : 2026-10-15 Epub Date: 2026-10-05 DOI: 10.1016/j.compbiomed.2026.111960

V. Nanammal, S. Rajalakshmi, V. Remya, S. Ranjith

引用次数: 0

Editor's Note: “Automatic motion artifact detection in electrodermal activity signals using 1D U-net architecture” [Comput. Biol. Med. 182 (2024), 109139] 编者注：“使用1D U-net架构的皮肤电活动信号自动运动伪影检测”[计算机]。医学杂志。中华医学杂志，2003,19(2):391 - 391。

IF 6.3 2区医学

Computers in biology and medicine Pub Date : 2026-10-15 Epub Date: 2026-10-10 DOI: 10.1016/j.compbiomed.2026.111985

Youngsun Kong, Md Billal Hossain, Andrew Peitzsch, Hugo F. Posada-Quintero, Ki H. Chon

引用次数: 0

Editor Note to article entitled “Drug repositioning and experimental validation for targeting ZZ domain of p62 as a cancer treatment” [Comput. Biol. Med. 188, (2025), 109757] 标题为“靶向p62 ZZ结构域作为癌症治疗的药物重新定位和实验验证”的文章编者注[Comput]。医学杂志。医学。188,(2025),109757]

IF 6.3 2区医学

Computers in biology and medicine Pub Date : 2026-10-15 Epub Date: 2026-10-06 DOI: 10.1016/j.compbiomed.2026.111976

引用次数: 0

Harnessing Annona muricata phytochemicals for multi-target cancer therapy: An integrated network pharmacology and in-silico study 利用村田番荔枝植物化学物质进行多靶点癌症治疗：综合网络药理学和计算机研究。

IF 6.3 2区医学

Computers in biology and medicine Pub Date : 2026-10-15 Epub Date: 2026-10-04 DOI: 10.1016/j.compbiomed.2026.111970

Shital M. Patil, Abhijit Das, Kalyani Asgaonkar, Kalirajan Rajagopal, Amruta Avalaskar, Gautam Gundecha, Krishna Shevate, Pranjal Gavali, Prerana Bhosale

{"title":"Harnessing Annona muricata phytochemicals for multi-target cancer therapy: An integrated network pharmacology and in-silico study","authors":"Shital M. Patil, Abhijit Das, Kalyani Asgaonkar, Kalirajan Rajagopal, Amruta Avalaskar, Gautam Gundecha, Krishna Shevate, Pranjal Gavali, Prerana Bhosale","doi":"10.1016/j.compbiomed.2026.111970","DOIUrl":"10.1016/j.compbiomed.2026.111970","url":null,"abstract":"<div><div>Lung and breast cancers are among the major causes of cancer-related morbidity and mortality worldwide. Both these cancers share several dysregulated molecular processes, including common oncogenic signaling pathways and molecular targets. Therefore, the current study focuses on the dual anticancer potential of <em>Annona muricata</em>. Natural products from medicinal plants are recognized as valuable sources of bioactive compounds with potential anticancer activity. In the present study, an integrated network pharmacology and in-silico approach was employed to identify potential phytoconstituents from <em>Annona muricata</em> against lung and breast cancers. Initially, 63 phytochemicals were collected from the IMPPAT database and screened using ADMET and toxicity prediction, resulting in nine compounds with favorable pharmacokinetic and safety profiles. Network pharmacology identified 12,321 common genes associated with both cancers, from which 209 potential targets were obtained. Protein–protein interaction analysis identified key hub genes, including HSP90AA1, MMP9, HIF1A, and MDM2, for molecular docking. Docking revealed that HIF-1α (PDB ID: 3KCX) provided the most favorable binding environment. Among the screened phytochemicals, (−)-Coreximine showed the strongest interaction with HIS199 and ASP201. MM-GBSA confirmed its highest binding affinity (−39.47 kcal/mol), while DFT and molecular dynamics simulations demonstrated stability and persistent binding. Overall, these computational findings suggest that (−)-Coreximine may attenuate cancer progression through modulation of HIF-1α-associated pathways and represents a promising natural lead for further investigation.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"216 ","pages":"Article 111970"},"PeriodicalIF":6.3,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149105067","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

Context-aware asymmetric ensembling for interpretable retinopathy of prematurity screening via active query and vascular attention 通过主动查询和血管注意筛选可解释的早产儿视网膜病变的上下文感知不对称集成。

IF 6.3 2区医学

Computers in biology and medicine Pub Date : 2026-10-15 Epub Date: 2026-09-22 DOI: 10.1016/j.compbiomed.2026.111945

Md. Mehedi Hassan, Taufiq Hasan

{"title":"Context-aware asymmetric ensembling for interpretable retinopathy of prematurity screening via active query and vascular attention","authors":"Md. Mehedi Hassan, Taufiq Hasan","doi":"10.1016/j.compbiomed.2026.111945","DOIUrl":"10.1016/j.compbiomed.2026.111945","url":null,"abstract":"<div><div>Retinopathy of Prematurity (ROP) is among the major causes of preventable childhood blindness. Automated screening remains challenging, primarily due to limited data availability and the complexity of the condition involving both structural staging and microvascular abnormalities. Current deep learning models depend heavily on large private datasets and passive multimodal fusion, which commonly fail to generalize to small, imbalanced public cohorts. We thus propose the Context-Aware Asymmetric Ensemble Model (CAA Ensemble) that simulates clinical reasoning through two specialized streams. First, the Multi-Scale Active Query Network (MS-AQNet) serves as a structure specialist, utilizing clinical contexts as dynamic query vectors to spatially control visual feature extraction for localization of the fibrovascular ridge. Secondly, VascuMIL encodes Vascular Topology Maps (VMAP) within a gated Multiple Instance Learning (MIL) network to precisely identify vascular tortuosity. A synergistic meta-learner aggregates these orthogonal signals to resolve diagnostic discordance across multiple objectives. Tested on a highly imbalanced cohort of 188 infants (6004 images), the framework attained state-of-the-art performance on two distinct clinical tasks: achieving a Macro F1-Score of 0.93 for Broad ROP staging and an AUC of 0.996 for Plus Disease detection. Crucially, the system features ‘Glass Box’ transparency through counterfactual attention heatmaps and vascular threat maps, proving that clinical metadata dictates the model’s visual search. Additionally, this study demonstrates that architectural inductive bias can serve as an effective bridge for the medical AI data gap.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"216 ","pages":"Article 111945"},"PeriodicalIF":6.3,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149105077","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

Retraction notice to "Performance optimization of support vector machine with oppositional grasshopper optimization for acute appendicitis diagnosis" [Computers in Biology and Medicine 143 (2022) 105206] “基于对立蚱蜢优化的支持向量机在急性阑尾炎诊断中的性能优化”[生物与医学计算机143(2022)105206]。

IF 6.3 2区医学

Computers in biology and medicine Pub Date : 2026-10-15 Epub Date: 2026-10-04 DOI: 10.1016/j.compbiomed.2026.111961

Jianfu Xia, Zhifei Wang, Daqing Yang, Rizeng Li, Guoxi Liang, Huiling Chen, Ali Asghar Heidari, Hamza Turabieh, Majdi Mafarja, Zhifang Pan

引用次数: 0