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Semantic uncertainty Guided Cross-Transformer for enhanced macular edema segmentation in OCT images Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-16 Hui Liu, Wenteng Gao, Lei Yang, Di Wu, Dehan Zhao, Kun Chen, Jicheng Liu, Yu Ye, Ronald X. Xu, Mingzhai Sun
Macular edema, a prevalent ocular complication observed in various retinal diseases, can lead to significant vision loss or blindness, necessitating accurate and timely diagnosis. Despite the potential of deep learning for segmentation of macular edema, challenges persist in accurately identifying lesion boundaries, especially in low-contrast and noisy regions, and in distinguishing between Inner Retinal
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Navigate biopsy with ultrasound under augmented reality device: Towards higher system performance Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-16 Haowei Li, Wenqing Yan, Jiasheng Zhao, Yuqi Ji, Long Qian, Hui Ding, Zhe Zhao, Guangzhi Wang
Biopsies play a crucial role in determining the classification and staging of tumors. Ultrasound is frequently used in this procedure to provide real-time anatomical information. Using augmented reality (AR), surgeons can visualize ultrasound data and spatial navigation information seamlessly integrated with real tissues. This innovation facilitates faster and more precise biopsy operations. We have
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PLS-based gene subset augmentation and tumor-specific gene identification Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-16 Wenjie You, Zijiang Yang, Guoli Ji
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Deep-learning-based real-time individualization for reduce-order haemodynamic model Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-15 Bao Li, Guangfei Li, Jincheng Liu, Hao Sun, Chuanqi Wen, Yang Yang, Aike Qiao, Jian Liu, Youjun Liu
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PT-Finder: A multi-modal neural network approach to target identification Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-15 Hossam Nada, Sungdo Kim, Kyeong Lee
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Predictive health monitoring: Leveraging artificial intelligence for early detection of infectious diseases in nursing home residents through discontinuous vital signs analysis Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-14 Alberto Garcés-Jiménez, María-Luz Polo-Luque, Juan A. Gómez-Pulido, Diego Rodríguez-Puyol, José M. Gómez-Pulido
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Verified localization and pharmacognosy of herbal medicinal plants in a combined network framework Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-13 Misaj Sharafudeen, Vinod Chandra S.S., Aswathy A.L., Asif Navas, Vismaya K.N.
Pharmacognosy from medicinal plants involves the scientific domain of medicinal compounding based on their medicinal properties. Accurate identification of medicinal plants is crucial, especially by examining their leaves. Choosing the wrong plant species for medicinal preparations can have adverse side effects. This study presents a Human-Centered Artificial Intelligence approach for medicinal plant
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Xiaoqing: A Q&A model for glaucoma based on LLMs Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-12 Xiaojuan Xue, Deshiwei Zhang, Chengyang Sun, Yiqiao Shi, Rongsheng Wang, Tao Tan, Peng Gao, Sujie Fan, Guangtao Zhai, Menghan Hu, Yue Wu
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One-shot skill assessment in high-stakes domains with limited data via meta learning Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-11 Erim Yanik, Steven Schwaitzberg, Gene Yang, Xavier Intes, Jack Norfleet, Matthew Hackett, Suvranu De
Deep Learning (DL) has achieved robust competency assessment in various high-stakes fields. However, the applicability of DL models is often hampered by their substantial data requirements and confinement to specific training domains. This prevents them from transitioning to new tasks where data is scarce. Therefore, domain adaptation emerges as a critical element for the practical implementation of
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Fuzzy machine learning logic utilization on hormonal imbalance dataset Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-11 Rabia Khushal, Ubaida Fatima
In this research work, a novel fuzzy data transformation technique has been proposed and applied to the hormonal imbalance dataset. Hormonal imbalance is ubiquitously found principally in females of reproductive age which ultimately leads to numerous related medical conditions. Polycystic Ovary Syndrome (PCOS) is one of them. Treatment along with adopting a healthy lifestyle is advised to mitigate
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Explosive weld joint characteristics of Copper-Tantalum via simulation Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-10 Van-Thuc Nguyen, Vo Thi Thu Nhu, Xuan-Tien Vo
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CRIECNN: Ensemble convolutional neural network and advanced feature extraction methods for the precise forecasting of circRNA-RBP binding sites Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-10 Dilan Lasantha, Sugandima Vidanagamachchi, Sam Nallaperuma
Circular RNAs (circRNAs) have surfaced as important non-coding RNA molecules in biology. Understanding interactions between circRNAs and RNA-binding proteins (RBPs) is crucial in circRNA research. Existing prediction models suffer from limited availability and accuracy, necessitating advanced approaches. In this study, we propose CRIECNN (ircular RNA-BP nteraction predictor using an nsemble onvolutional
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Enhancing gait cadence through rhythm-modulated music: A study on healthy adults Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-10 Aboubakr Samadi, Javad Rasti, Mehran Emadi Andani
Gait disorders stemming from brain lesions or chemical imbalances, pose significant challenges for patients. Proposed treatments encompass medication, deep brain stimulation, physiotherapy, and visual stimulation. Music, with its harmonious structures, serves as a continuous reference, synchronizing muscle activities through neural connections between hearing and motor functions, can show promise in
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Hepatic steatosis modeling and MRI signal simulations for comparison of single- and dual-R2* models and estimation of fat fraction at 1.5T and 3T Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-10 Utsav Shrestha, Juan P. Esparza, Sanjaya K. Satapathy, Jason M. Vanatta, Zachary R. Abramson, Aaryani Tipirneni-Sajja
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Effect of degradation in polymer scaffolds on mechanical properties: Surface vs. bulk erosion Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-10 Nataliya Elenskaya, Polina Koryagina, Mikhail Tashkinov, Vadim V. Silberschmidt
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Anatomically aware dual-hop learning for pulmonary embolism detection in CT pulmonary angiograms Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-09 Florin Condrea, Saikiran Rapaka, Lucian Itu, Puneet Sharma, Jonathan Sperl, A. Mohamed Ali, Marius Leordeanu
Pulmonary Embolisms (PE) represent a leading cause of cardiovascular death. While medical imaging, through computed tomographic pulmonary angiography (CTPA), represents the gold standard for PE diagnosis, it is still susceptible to misdiagnosis or significant diagnosis delays, which may be fatal for critical cases. Despite the recently demonstrated power of deep learning to bring a significant boost
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A multi-instance tumor subtype classification method for small PET datasets using RA-DL attention module guided deep feature extraction with radiomics features Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-09 Zhaoshuo Diao, Huiyan Jiang
Positron emission tomography (PET) is extensively employed for diagnosing and staging various tumors, including liver cancer, lung cancer, and lymphoma. Accurate subtype classification of tumors plays a crucial role in formulating effective treatment plans for patients. Notably, lymphoma comprises subtypes like diffuse large B-cell lymphoma and Hodgkin’s lymphoma, while lung cancer encompasses adenocarcinoma
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Digital dual test syphilis/HIV detection based on Fourier Descriptors of Cyclic Voltammetry curves Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-09 Ignacio Sanchez-Gendriz, Dionísio D.A. Carvalho, Leonardo J. Galvão-Lima, Ana Isabela Lopes Sales-Moioli, Talita Brito, Felipe Fernandes, Jorge Henriques, Thaisa Lima, Luiz Affonso Guedes, Agnaldo S. Cruz, Antonio H.F. Morais, João Paulo Q. Santos, Ernano Arrais, Karilany Dantas Coutinho, Guilherme Medeiros Machado, Aliete Cunha-Oliveira, Catarina Alexandra dos Reis Vale Gomes, Ricardo A.M. Valentim
Effective and timely detection is vital for mitigating the severe impacts of Sexually Transmitted Infections (STI), including syphilis and HIV. Cyclic Voltammetry (CV) sensors have shown promise as diagnostic tools for these STI, offering a pathway towards cost-effective solutions in primary health care settings. This study aims to pioneer the use of Fourier Descriptors (FDs) in analyzing CV curves
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New non-local mean methods for MRI denoising based on global self-similarity between values Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-09 Shiao Li, Fei Wang, Song Gao
Magnetic resonance imaging (MRI) is a non-invasive medical imaging technique that provides high-resolution 3D images and valuable insights into human tissue conditions. Even at present, the refinement of denoising methods for MRI remains a crucial concern for improving the quality of the images. This study aims to improve the prefiltered rotationally invariant non-local principal component analysis
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Edge-relational window-attentional graph neural network for gene expression prediction in spatial transcriptomics analysis Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-09 Cui Chen, Zuping Zhang, Panrui Tang, Xin Liu, Bo Huang
Spatial transcriptomics (ST), containing gene expression with fine-grained (, different windows) spatial location within tissue samples, has become vital in developing innovative treatments. Traditional ST technology, however, rely on costly specialized commercial equipment. Addressing this, our article aims to creates a cost-effective, virtual ST approach using standard tissue images for gene expression
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Cross-patch feature interactive net with edge refinement for retinal vessel segmentation Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-09 Ning Kang, Maofa Wang, Cheng Pang, Rushi Lan, Bingbing Li, Junlin Guan, Huadeng Wang
Retinal vessel segmentation based on deep learning is an important auxiliary method for assisting clinical doctors in diagnosing retinal diseases. However, existing methods often produce mis-segmentation when dealing with low contrast images and thin blood vessels, which affects the continuity and integrity of the vessel skeleton. In addition, existing deep learning methods tend to lose a lot of detailed
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Stack-AAgP: Computational prediction and interpretation of anti-angiogenic peptides using a meta-learning framework Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-09 Saima Gaffar, Hilal Tayara, Kil To Chong
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A novel approach to the detection of facial wrinkles: Database, detection algorithm, and evaluation metrics Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-09 Zijia Liu, Quan Qi, Sijia Wang, Guangtao Zhai
Skin wrinkles result from intrinsic aging processes and extrinsic influences, including prolonged exposure to ultraviolet radiation and tobacco smoking. Hence, the identification of wrinkles holds significant importance in skin aging and medical aesthetic investigation. Nevertheless, current methods lack the comprehensiveness to identify facial wrinkles, particularly those that may appear insignificant
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On the use of contrastive learning for standard-plane classification in fetal ultrasound imaging Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-09 Giovanna Migliorelli, Maria Chiara Fiorentino, Mariachiara Di Cosmo, Francesca Pia Villani, Adriano Mancini, Sara Moccia
To investigate the effectiveness of contrastive learning, in particular SimClr, in reducing the need for large annotated ultrasound (US) image datasets for fetal standard plane identification. We explore SimClr advantage in the cases of both low and high inter-class variability, considering at the same time how classification performance varies according to different amounts of labels used. This evaluation
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S2DA-Net: Spatial and spectral-learning double-branch aggregation network for liver tumor segmentation in CT images Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-09 Huaxiang Liu, Jie Yang, Chao Jiang, Sailing He, Youyao Fu, Shiqing Zhang, Xudong Hu, Jiangxiong Fang, Wenbin Ji
Accurate liver tumor segmentation is crucial for aiding radiologists in hepatocellular carcinoma evaluation and surgical planning. While convolutional neural networks (CNNs) have been successful in medical image segmentation, they face challenges in capturing long-term dependencies among pixels. On the other hand, Transformer-based models demand a high number of parameters and involve significant computational
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Vislocas: Vision transformers for identifying protein subcellular mis-localization signatures of different cancer subtypes from immunohistochemistry images Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-09 Jing-Wen Wen, Han-Lin Zhang, Pu-Feng Du
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An efficient Parkinson's disease detection framework: Leveraging time-frequency representation and AlexNet convolutional neural network Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-09 Siuly Siuly, Smith K. Khare, Enamul Kabir, Muhammad Tariq Sadiq, Hua Wang
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Enhancing cross-subject EEG emotion recognition through multi-source manifold metric transfer learning Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-09 XinSheng Shi, Qingshan She, Feng Fang, Ming Meng, Tongcai Tan, Yingchun Zhang
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Fine-Grained Self-Supervised Learning with Jigsaw puzzles for medical image classification Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-08 Wongi Park, Jongbin Ryu
Classifying fine-grained lesions is challenging due to minor and subtle differences in medical images. This is because learning features of fine-grained lesions with highly minor differences is very difficult in training deep neural networks. Therefore, in this paper, we introduce ine-rained elf-upervised earning() method for classifying subtle lesions in medical images. The proposed method progressively
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Unraveling the distinction between depression and anxiety: A machine learning exploration of causal relationships Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-08 Tiantian Wang, Chuang Xue, Zijian Zhang, Tingting Cheng, Guang Yang
Depression and anxiety, prevalent coexisting mood disorders, pose a clinical challenge in accurate differentiation, hindering effective healthcare interventions. This research addressed this gap by employing a streamlined Symptom Checklist 90 (SCL-90) designed to minimize patient response burden. Utilizing machine learning algorithms, the study sought to construct classification models capable of distinguishing
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Prediction of drug-target binding affinity based on deep learning models Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-08 Hao Zhang, Xiaoqian Liu, Wenya Cheng, Tianshi Wang, Yuanyuan Chen
The prediction of drug-target binding affinity (DTA) plays an important role in drug discovery. Computerized virtual screening techniques have been used for DTA prediction, greatly reducing the time and economic costs of drug discovery. However, these techniques have not succeeded in reversing the low success rate of new drug development. In recent years, the continuous development of deep learning
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Comprehensive analysis reveals that LTBR is a immune-related biomarker for glioma Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-08 Qisheng Tang, Yifan Yuan, Lingjuan Li, Yue Xu, Wei Ji, Siyu Xiao, Yi Han, Wenrong Miao, Jing Cai, Pu You, Ming Chen, Saineng Ding, Zhen Li, Zengxin Qi, Weiliang Hou, Hao Luo
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Early prediction of long hospital stay for Intensive Care units readmission patients using medication information Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-08 Min Zhang, Tsung-Ting Kuo
Predicting Intensive Care Unit (ICU) Length of Stay (LOS) accurately can improve patient wellness, hospital operations, and the health system's financial status. This study focuses on predicting the prolonged ICU LOS (≥3 days) of the 2nd admission, utilizing short historical data (1st admission only) for early-stage prediction, as well as incorporating medication information. We selected 18,572 ICU
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A new family of instance-level loss functions for improving instance-level segmentation and detection of white matter hyperintensities in routine clinical brain MRI Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-08 Muhammad Febrian Rachmadi, Michal Byra, Henrik Skibbe
In this study, we introduce “instance loss functions”, a new family of loss functions designed to enhance the training of neural networks in the instance-level segmentation and detection of objects in biomedical image data, particularly those of varied numbers and sizes. Intended to be utilized conjointly with traditional loss functions, these proposed functions, prioritize object instances over pixel-by-pixel
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Dynamic graph transformer network via dual-view connectivity for autism spectrum disorder identification Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-07 Zihao Guan, Jiaming Yu, Zhenshan Shi, Xiumei Liu, Renping Yu, Taotao Lai, Changcai Yang, Heng Dong, Riqing Chen, Lifang Wei
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Computer aided diagnosis of diabetic retinopathy based on multi-view joint learning Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-06 Xuebin Xu, Dehua Liu, Guohua Huang, Muyu Wang, Meng Lei, Yang Jia
Diabetic retinopathy (DR) is a kind of ocular complication of diabetes, and its degree grade is an essential basis for early diagnosis of patients. Manual diagnosis is a long and expensive process with a specific risk of misdiagnosis. Computer-aided diagnosis can provide more accurate and practical treatment recommendations. In this paper, we propose a multi-view joint learning DR diagnostic model
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Tumor conspicuity enhancement-based segmentation model for liver tumor segmentation and RECIST diameter measurement in non-contrast CT images Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-06 Haofeng Liu, Yanyan Zhou, Shuiping Gou, Zhonghua Luo
Liver tumor segmentation (LiTS) accuracy on contrast-enhanced computed tomography (CECT) images is higher than that on non-contrast computed tomography (NCCT) images. However, CECT requires contrast medium and repeated scans to obtain multiphase enhanced CT images, which is time-consuming and cost-increasing. Therefore, despite the lower accuracy of LiTS on NCCT images, which still plays an irreplaceable
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recruIT: A cloud-native clinical trial recruitment support system based on Health Level 7 Fast Healthcare Interoperability Resources (HL7 FHIR) and the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-06 Christian Gulden, Philipp Macho, Ines Reinecke, Cosima Strantz, Hans-Ulrich Prokosch, Romina Blasini
Clinical trials (CTs) are foundational to the advancement of evidence-based medicine and recruiting a sufficient number of participants is one of the crucial steps to their successful conduct. Yet, poor recruitment remains the most frequent reason for premature discontinuation or costly extension of clinical trials. We designed and implemented a novel, open-source software system to support the recruitment
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Accurate estimation of the inhibition zone of antibiotics based on laser speckle imaging and multiple random speckle illumination Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-06 Donghyeok Kim, Jongseo Lee, Jonghee Yoon
The antimicrobial susceptibility test (AST) plays a crucial role in selecting appropriate antibiotics for the treatment of bacterial infections in patients. The diffusion disk method is widely adopted AST method due to its simplicity, cost-effectiveness, and flexibility. It assesses antibiotic efficacy by measuring the size of the inhibition zone where bacterial growth is suppressed. Quantification
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Symptom-based drug prediction of lifestyle-related chronic diseases using unsupervised machine learning techniques Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-05 Sudipto Bhattacharjee, Banani Saha, Sudipto Saha
Lifestyle-related diseases (LSDs) impose a substantial economic burden on patients and health care services. LSDs are chronic in nature and can directly affect the heart and lungs. Therapeutic interventions only based on symptoms can be crucial for prompt treatment initiation in LSDs, as symptoms are the first information available to clinicians. So, this work aims to apply unsupervised machine learning
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Evaluation of the mechanical behaviour of the expandable wedge locked nail fixation in retrograde use: A finite element study Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-05 Mustafa Özkaya, Teyfik Demir
In literature, there have been many studies conducted to research the alternatives of standard interlocking intramedullary nailing. The expandable wedge locked nail fixation, which is thought as a new alternative to the standard interlocking nailing, has been presented in previous numerical studies. The antegrade usage of the wedge locked nail fixation has provided promising results. From this point
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Source-free active domain adaptation for diabetic retinopathy grading based on ultra-wide-field fundus images Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-05 Jinye Ran, Guanghua Zhang, Fan Xia, Ximei Zhang, Juan Xie, Hao Zhang
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Assessing the reproducibility of machine-learning-based biomarker discovery in Parkinson’s disease Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-05 Ali Ameli, Lourdes Peña-Castillo, Hamid Usefi
Feature selection and machine learning algorithms can be used to analyze Single Nucleotide Polymorphisms (SNPs) data and identify potential disease biomarkers. Reproducibility of identified biomarkers is critical for them to be useful for clinical research; however, genotyping platforms and selection criteria for individuals to be genotyped affect the reproducibility of identified biomarkers. To assess
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Sa-TTCA: An SVM-based approach for tumor T-cell antigen classification using features extracted from biological sequencing and natural language processing Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-04 Thi-Oanh Tran, Nguyen Quoc Khanh Le
Accurately predicting tumor T-cell antigen (TTCA) sequences is a crucial task in the development of cancer vaccines and immunotherapies. TTCAs derived from tumor cells, are presented to immune cells (T cells) through major histocompatibility complex (MHC), via the recognition of specific portions of their structure known as epitopes. More specifically, MHC class I introduces TTCAs to T-cell receptors
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Registration of multimodal bone images based on edge similarity metaheuristic Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-04 Dibin Zhou, Chen Yu, Wenhao Liu, Fuchang Liu
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3-D finite element model of the impaction of a press-fitted femoral stem under various biomechanical environments Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-03 Anne-Sophie Poudrel, Arthur Bouffandeau, Giuseppe Rosi, Arnaud Dubory, Charles-Henri Flouzat Lachaniette, Vu-Hieu Nguyen, Guillaume Haiat
Uncemented femoral stem insertion into the bone is achieved by applying successive impacts on an inserter tool called “ancillary”. Impact analysis has shown to be a promising technique to monitor the implant insertion and to improve its primary stability. This study aims to provide a better understanding of the dynamic phenomena occurring between the hammer, the ancillary, the implant and the bone
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Boosting predictive models and augmenting patient data with relevant genomic and pathway information Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-03 Samuele Buosi, Mohan Timilsina, Maria Torrente, Mariano Provencio, Dirk Fey, Vít Nováček
The recurrence of low-stage lung cancer poses a challenge due to its unpredictable nature and diverse patient responses to treatments. Personalized care and patient outcomes heavily rely on early relapse identification, yet current predictive models, despite their potential, lack comprehensive genetic data. This inadequacy fuels our research focus—integrating specific genetic information, such as pathway
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Generating lymphoma ultrasound image description with transformer model Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-03 Jinyi Deng, Dehua Chen, Chunlin Zhang, Yijie Dong
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Identification and classification of glioma subtypes based on RNA-binding proteins Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-03 Xudong Liu, Lei Wu, Lei Wang, Yongsheng Li
Glioma is a common and aggressive primary malignant cancer known for its high morbidity, mortality, and recurrence rates. Despite this, treatment options for glioma are currently restricted. The dysregulation of RBPs has been linked to the advancement of several types of cancer, but their precise role in glioma evolution is still not fully understood. This study sought to investigate how RBPs may impact
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PhosMap: An ensemble bioinformatic platform to empower interactive analysis of quantitative phosphoproteomics Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-02 Mengsha Tong, Zan Liu, Jiaao Li, Xin Wei, Wenhao Shi, Chenyu Liang, Chunyu Yu, Rongting Huang, Yuxiang Lin, Xinkang Wang, Shun Wang, Yi Wang, Jialiang Huang, Yini Wang, Tingting Li, Jun Qin, Dongdong Zhan, Zhi-Liang Ji
Liquid chromatography-mass spectrometry (LC-MS)-based quantitative phosphoproteomics has been widely used to detect thousands of protein phosphorylation modifications simultaneously from the biological specimens. However, the complicated procedures for analyzing phosphoproteomics data has become a bottleneck to widening its application. Here, we develop PhosMap, a versatile and scalable tool to accomplish
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H2MaT-Unet:Hierarchical hybrid multi-axis transformer based Unet for medical image segmentation Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-02 ZhiYong Ju, ZhongChen Zhou, ZiXiang Qi, Cheng Yi
Accurate segmentation and lesion localization are essential for treating diseases in medical images. Despite deep learning methods enhancing segmentation, they still have limitations due to convolutional neural networks’ inability to capture long-range feature dependencies. The self-attention mechanism in Transformers addresses this drawback, but high-resolution images present computational complexity
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A mathematical model of tissue axial and radial diffusion in the microvasculature for intravascular microscopy and phosphorescence quenching data Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-02 Vinay P. Jani, Vivek P. Jani, Carlos Munoz, Pedro Cabrales
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NFMCLDA: Predicting miRNA-based lncRNA-disease associations by network fusion and matrix completion Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-02 Yibing Ma, Yongle Shi, Xiang Chen, Bai Zhang, Hanwen Wu, Jie Gao
In recent years, emerging evidence has revealed a strong association between dysregulations of long non-coding RNAs (lncRNAs) and sophisticated human diseases. Biological experiments are adequate to identify such associations, but they are costly and time-consuming. Therefore, developing high-quality computational methods is a challenging and urgent task in the field of bioinformatics. This paper proposes
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Exploring the muscle architecture effect on the mechanical behaviour of mouse rotator cuff muscles Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-02 A. Heras-Sádaba, A. Pérez-Ruiz, P. Martins, C. Ederra, C. Ortiz de Solórzano, G. Abizanda, J. Pons-Villanueva, B. Calvo, J. Grasa
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Structure-based virtual screening of novel USP5 inhibitors targeting the zinc finger ubiquitin-binding domain Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-02 Tianhao Wang, Jianbo Tong, Xing Zhang, Zhe Wang, Lei Xu, Peichen Pan, Tingjun Hou
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Machine learning model based on RCA-PDCA nursing methods and differentiating factors to predict hypotension during cesarean section surgery Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-02 Xue Yang, Yu-Mei Li, Qiong Wang, Run Li, Ping Zhang
Intraoperative hypotension during cesarean section has become a serious complication for maternal and fetal healthy. It is commonly encountered by subarachnoid anesthesia. However, currently used control methods have varying degrees of side effects, such as drugs. The Root Cause Analysis (RCA) - Plan, Do, Check, Act (PDCA) is a new model of care that identifies the root causes of problems. The study
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DP-GAN+B: A lightweight generative adversarial network based on depthwise separable convolutions for generating CT volumes Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-02 Xinlong Xing, Xiaosen Li, Chaoyi Wei, Zhantian Zhang, Ou Liu, Senmiao Xie, Haoman Chen, Shichao Quan, Cong Wang, Xin Yang, Xiaoming Jiang, Jianwei Shuai
X-rays, commonly used in clinical settings, offer advantages such as low radiation and cost-efficiency. However, their limitation lies in the inability to distinctly visualize overlapping organs. In contrast, Computed Tomography (CT) scans provide a three-dimensional view, overcoming this drawback but at the expense of higher radiation doses and increased costs. Hence, from both the patient's and hospital's
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Eye movement analysis for real-world settings using segmented linear regression Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-02 Kritika Johari, Rishabh Bhardwaj, Jung-Jae Kim, Wei Quin Yow, U-Xuan Tan
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Unlocking the potential: A novel prognostic index signature for acute myeloid leukemia Comput. Biol. Med. (IF 7.7) Pub Date : 2024-04-01 Lu-Qiang Zhang, Yu-Chao Liang, Jun-Xuan Wang, Jing Zhang, Ta La, Qian-Zhong Li
Acute myeloid leukemia (AML) is an aggressive malignancy characterized by challenges in treatment, including drug resistance and frequent relapse. Recent research highlights the crucial roles of tumor microenvironment (TME) in assisting tumor cell immune escape and promoting tumor aggressiveness. This study delves into the interplay between AML and TME. Through the exploration of potential driver genes
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A fusion architecture to deliver multipurpose mobile health services Comput. Biol. Med. (IF 7.7) Pub Date : 2024-03-30 Ana González Bermúdez, David Carramiñana, Ana M. Bernardos, Luca Bergesio, Juan A. Besada
Mobile Health (mHealth) services typically make use of customized software architectures, leading to development-dependent fragmentation. Nevertheless, irrespective of their specific purpose, most mHealth services share common functionalities, where standard pieces could be reused or adapted to expedite service deployment and even extend the follow-up of appearing conditions under the same service