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- research-articleSeptember 2024
From pixels to druggable leads: A CADD strategy for the design and synthesis of potent DDR1 inhibitors
Computer Methods and Programs in Biomedicine (CBIO), Volume 254, Issue Chttps://doi.org/10.1016/j.cmpb.2024.108318Highlights- CADD optimization of virtual hit (4a) to potent DDR1 inhibitors.
- 2 × 1000 ns MD reveals key binding pocket for DDR1.
- 12 novel DDR1 derivatives yielded SAR.
- Compound 4c: promising lead for DDR1 (0.11 µM).
- Streamlined ...
While numerous in silico tools exist for target-based drug discovery, the inconsistent integration of in vitro data with predictive models hinders research and development productivity. This is particularly apparent ...
- research-articleSeptember 2024
Automatic semantic segmentation of EHG recordings by deep learning: An approach to a screening tool for use in clinical practice
- Félix Nieto-del-Amor,
- Yiyao Ye-Lin,
- Rogelio Monfort-Ortiz,
- Vicente Jose Diago-Almela,
- Fernando Modrego-Pardo,
- Jose L. Martinez-de-Juan,
- Dongmei Hao,
- Gema Prats-Boluda
Computer Methods and Programs in Biomedicine (CBIO), Volume 254, Issue Chttps://doi.org/10.1016/j.cmpb.2024.108317Highlights- A deep learning-based automatic semantic segmentation of EHG recordings is proposed.
- A screening tool for physiological EHG epoch segmentation in clinical practice.
- The best architecture for detecting physiological epochs was UNET ...
Preterm delivery is an important factor in the disease burden of the newborn and infants worldwide. Electrohysterography (EHG) has become a promising technique for predicting this condition, thanks to its high degree of ...
- research-articleSeptember 2024
Pleural lung sliding quantification using a speckle tracking technology: A feasibility study on 30 healthy volunteers
- Gary Duclos,
- Ludivine Marecal,
- Noemie Resseguier,
- Martin Postzich,
- Chloe Taguet,
- Sami Hraiech,
- Marc Leone,
- Laurent Müller,
- Laurent Zieleskiewicz
Computer Methods and Programs in Biomedicine (CBIO), Volume 254, Issue Chttps://doi.org/10.1016/j.cmpb.2024.108316Hightlights- Lung over distention is a major concern for patients under mechanical ventilation.
- Clinician is lacking a bedside tool able to quantify the regional lung distension.
- Lung ultrasound is be able to quantify pleural sliding using ...
Speckle tracking technology quantifies lung sliding and detects lung sliding abolition in case of pneumothorax on selected ultrasound loops through the analysis of acoustic markers.
ObjectivesWe aimed to test the ability of speckle ...
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- research-articleSeptember 2024
CPSS: Fusing consistency regularization and pseudo-labeling techniques for semi-supervised deep cardiovascular disease detection using all unlabeled electrocardiograms
Computer Methods and Programs in Biomedicine (CBIO), Volume 254, Issue Chttps://doi.org/10.1016/j.cmpb.2024.108315Abstract Background and objective:Deep learning usually achieves good performance in the supervised way, which requires a large amount of labeled data. However, manual labeling of electrocardiograms (ECGs) is laborious that requires much medical ...
Highlights- Fusing consistency regularization and pseudo-labeling for CVD detection.
- Utilizing all unlabeled ECGs in semi-supervised learning.
- Deploying the CVD detection algorithm to a heterogeneous SoC.
- The scheme has good potential for ...
- research-articleSeptember 2024
Survival prediction in second primary breast cancer patients with machine learning: An analysis of SEER database
Computer Methods and Programs in Biomedicine (CBIO), Volume 254, Issue Chttps://doi.org/10.1016/j.cmpb.2024.108310Highlights- Random survival forest can accurately predict overall survival of SPBC patients.
- Age was the most important predictor for overall survival prediction.
- Our prediction model showed good fairness in different subgroups of the ...
Studies have found that first primary cancer (FPC) survivors are at high risk of developing second primary breast cancer (SPBC). However, there is a lack of prognostic studies specifically focusing on patients with SPBC.
MethodsThis ...
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- research-articleSeptember 2024
Advanced OCTA imaging segmentation: Unsupervised, non-linear retinal vessel detection using modified self-organizing maps and joint MGRF modeling
- Ahmed Alksas,
- Ahmed Sharafeldeen,
- Hossam Magdy Balaha,
- Mohammad Z. Haq,
- Ali Mahmoud,
- Mohamed Ghazal,
- Norah Saleh Alghamdi,
- Marah Alhalabi,
- Jawad Yousaf,
- Harpal Sandhu,
- Ayman El-Baz
Computer Methods and Programs in Biomedicine (CBIO), Volume 254, Issue Chttps://doi.org/10.1016/j.cmpb.2024.108309Abstract Background and Objective:This paper proposes a fully automated and unsupervised stochastic segmentation approach using two-level joint Markov-Gibbs Random Field (MGRF) to detect the vascular system from retinal Optical Coherence Tomography ...
Highlights- Applied fully automated, unsupervised learning for retinal OCTA images segmentation.
- Employed a two-level joint MGRF and LCDG model to improve segmentation accuracy.
- Enhanced the model’s precision and reliability with a modified EM ...
- research-articleSeptember 2024
A deep learning approach for overall survival prediction in lung cancer with missing values
Computer Methods and Programs in Biomedicine (CBIO), Volume 254, Issue Chttps://doi.org/10.1016/j.cmpb.2024.108308Abstract Background and Objective:In the field of lung cancer research, particularly in the analysis of overall survival (OS), artificial intelligence (AI) serves crucial roles with specific aims. Given the prevalent issue of missing data in the medical ...
Highlights
- A DL-based decision support system predicting lung cancer prognosis.
- A transformer-based approach to cope with missing values without imputation.
- A model robust across different time granularities used to predict overall survival.
- research-articleSeptember 2024
Influence of genetic mutations to atria vulnerability to atrial fibrillation: An in-silico 3D human atria study
Computer Methods and Programs in Biomedicine (CBIO), Volume 254, Issue Chttps://doi.org/10.1016/j.cmpb.2024.108307Highlights- Comprehensive study to analyse the effects of genetic mutations on K + channels on a 3D atrial models.
- Analysis of the impact of genetic mutations on a realistic, patient-specific 3D atrial geometry.
- Extensive study to assess ...
Personalized 3D computer models of atria have been extensively implemented in the last yearsas a tool to facilitate the understanding of the mechanisms underlying different forms of arrhythmia, such as atrial fibrillation ...
- research-articleSeptember 2024
Memory impacts in hepatitis C: A global analysis of a fractional-order model with an effective treatment
- Parvaiz Ahmad Naik,
- Mehmet Yavuz,
- Sania Qureshi,
- Mehraj-ud-din Naik,
- Kolade M. Owolabi,
- Amanullah Soomro,
- Abdul Hamid Ganie
Computer Methods and Programs in Biomedicine (CBIO), Volume 254, Issue Chttps://doi.org/10.1016/j.cmpb.2024.108306Abstract Background and objective:Hepatitis virus infections are affecting millions of people worldwide, causing death, disability, and considerable expenditure. Chronic infection with hepatitis C virus (HCV) can cause severe public health problems ...
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Highlights- The global dynamics of a fractional-order Hepatitis C virus (HCV) model with an effective treatment are investigated.
- The fixed points of the model are identified and the stability analysis is carried out.
- The fractional Adams ...
- research-articleSeptember 2024
EMG-based prediction of step direction for a better control of lower limb wearable devices
Computer Methods and Programs in Biomedicine (CBIO), Volume 254, Issue Chttps://doi.org/10.1016/j.cmpb.2024.108305Highlights- A Toe-off intention decoder based on an SVM algorithm and sEMG signals has been proposed to detect step initiation intention independently from step direction.
- A directional EMG decoder based on an SVM algorithm and sEMG signals has ...
Lower-limb wearable devices can significantly improve the quality of life of subjects suffering from debilitating conditions, such as amputations, neurodegenerative disorders, and stroke-related impairments. Current ...
- research-articleSeptember 2024
Suppressing the HIFU interference in ultrasound guiding images with a diffusion-based deep learning model
Computer Methods and Programs in Biomedicine (CBIO), Volume 254, Issue Chttps://doi.org/10.1016/j.cmpb.2024.108304Highlights- In this study, we proposed a novel diffusion-based deep learning (DL) model (HIFU-Diff) for suppressing the HIFU interference in the ultrasound guiding images.
- The HIFU-Diff network can achieve superior performance in preserving fine ...
In ultrasound guided high-intensity focused ultrasound (HIFU) surgery, it is necessary to transmit sound waves at different frequencies simultaneously using two transducers: one for the HIFU therapy and another for the ...
- research-articleSeptember 2024
Role of the vessel morphology on the lenticulostriate arteries hemodynamics during atrial fibrillation: A CFD-based multivariate regression analysis
- Andrea Saglietto,
- Francesco Tripoli,
- Jaco Zwanenburg,
- Geert Jan Biessels,
- Gaetano Maria De Ferrari,
- Matteo Anselmino,
- Luca Ridolfi,
- Stefania Scarsoglio
Computer Methods and Programs in Biomedicine (CBIO), Volume 254, Issue Chttps://doi.org/10.1016/j.cmpb.2024.108303Highlights- Hemodynamic alterations due to atrial fibrillation (AF) increase the risk of dementia.
- Lenticulostriate arteries (LSAs) are susceptible to vascular dementia development.
- We combined MRI-based computational fluid dynamics and ...
Atrial fibrillation (AF) is the most common cardiac arrhythmia, inducing accelerated and irregular beating. Beside well-known disabling symptoms - such as palpitations, reduced exercise tolerance, and chest discomfort - ...
- research-articleSeptember 2024
Development of AI-generated medical responses using the ChatGPT for cancer patients
- Jae-woo Lee,
- In-Sang Yoo,
- Ji-Hye Kim,
- Won Tae Kim,
- Hyun Jeong Jeon,
- Hyo-Sun Yoo,
- Jae Gwang Shin,
- Geun-Hyeong Kim,
- ShinJi Hwang,
- Seung Park,
- Yong-June Kim
Computer Methods and Programs in Biomedicine (CBIO), Volume 254, Issue Chttps://doi.org/10.1016/j.cmpb.2024.108302Highlights- An effective health-information delivery can be an solution to the unsatisfied health information needs of patients.
- In this study, we developed a healthcare chatbot service (AI-guide bot) that conducts real-time conversations to ...
To develop a healthcare chatbot service (AI-guided bot) that conducts real-time conversations using large language models to provide accurate health information to patients.
MethodsTo provide accurate and specialized ...
- research-articleSeptember 2024
pyCEPS: A cross-platform electroanatomic mapping data to computational model conversion platform for the calibration of digital twin models of cardiac electrophysiology
- Robert Arnold,
- Anton J. Prassl,
- Aurel Neic,
- Franz Thaler,
- Christoph M. Augustin,
- Matthias A.F. Gsell,
- Karli Gillette,
- Martin Manninger,
- Daniel Scherr,
- Gernot Plank
Computer Methods and Programs in Biomedicine (CBIO), Volume 254, Issue Chttps://doi.org/10.1016/j.cmpb.2024.108299Abstract Background and Objective:Data from electro-anatomical mapping (EAM) systems are playing an increasingly important role in computational modeling studies for the patient-specific calibration of digital twin models. However, data exported from ...
Highlights
- An open-source framework for managing electro-anatomical mapping data.
- Access and interrogate mapping data exported from clinical mapping systems.
- Conversion to modeling formats according to the openCARP standard.
- Make the ...
- research-articleSeptember 2024
Haemosync: A synchronisation algorithm for multimodal haemodynamic signals
Computer Methods and Programs in Biomedicine (CBIO), Volume 254, Issue Chttps://doi.org/10.1016/j.cmpb.2024.108298Highlights- Time-shifts between haemodynamic signals lead to errors in multimodal signal analysis.
- Time-shifts may not be noticed visually, but can be detected and corrected.
- Algorithm automatically corrects drifts up to 1 s/min and time-...
Synchronous acquisition of haemodynamic signals is crucial for their multimodal analysis, such as dynamic cerebral autoregulation (DCA) analysis of arterial blood pressure (ABP) and transcranial Doppler (TCD)-derived cerebral blood ...
- research-articleSeptember 2024
A simulation study of transcranial magnetoacoustic stimulation of the basal ganglia thalamic neural network to improve pathological beta oscillations in Parkinson's disease
- Yanqiu Zhang,
- Hao Zhang,
- Tianya Xu,
- Jiahe Liu,
- Jiayang Mu,
- Rongjie Chen,
- Jiumin Yang,
- Peiguo Wang,
- Xiqi Jian
Computer Methods and Programs in Biomedicine (CBIO), Volume 254, Issue Chttps://doi.org/10.1016/j.cmpb.2024.108297Highlights- TMAS-STN has a better effect on PD state inhibition than TMAS-GPi.
- TMAS multinuclear stimulation is better than mononuclear stimulation for PD inhibition.
- Ultrasound can facilitate or inhibit the stimulatory effects of electrical ...
Parkinson's disease (PD) is a common neurodegenerative disease. Transcranial magnetoacoustic stimulation (TMAS) is a new therapy that combines a transcranial focused acoustic pressure field with a magnetic field to excite or inhibit ...
- research-articleSeptember 2024
Impact of geometric and hemodynamic changes on a mechanobiological model of atherosclerosis
Computer Methods and Programs in Biomedicine (CBIO), Volume 254, Issue Chttps://doi.org/10.1016/j.cmpb.2024.108296Abstract Background and Objective:In this work, the analysis of the importance of hemodynamic updates on a mechanobiological model of atheroma plaque formation is proposed.
Methods:For that, we use an idealized and axisymmetric model of carotid artery. ...
Highlights- Implemented geometry and hemodynamic updates to improve a validated atheroma plaque growth model.
- Demonstrated the importance of hemodynamic updates in a model of atheroma plaque formation (with or without endothelial repair).
- ...
- research-articleSeptember 2024
Multi-omics deep learning for radiation pneumonitis prediction in lung cancer patients underwent volumetric modulated arc therapy
- Wanyu Su,
- Dezhi Cheng,
- Weihua Ni,
- Yao Ai,
- Xianwen Yu,
- Ninghang Tan,
- Jianping Wu,
- Wen Fu,
- Chenyu Li,
- Congying Xie,
- Meixiao Shen,
- Xiance Jin
Computer Methods and Programs in Biomedicine (CBIO), Volume 254, Issue Chttps://doi.org/10.1016/j.cmpb.2024.108295Highlights- Predicting radiation pneumonitis in lung cancer patients undergoing radiotherapy helps improve the management of lung cancer patients.
- Combining dosiomics, radiomics, and deep learning enhances the prediction of radiation pneumonitis ...
To evaluate the feasibility and accuracy of radiomics, dosiomics, and deep learning (DL) in predicting Radiation Pneumonitis (RP) in lung cancer patients underwent volumetric modulated arc therapy (VMAT) to improve ...
- research-articleSeptember 2024
Dual model transfer learning to compensate for individual variability in brain-computer interface
Computer Methods and Programs in Biomedicine (CBIO), Volume 254, Issue Chttps://doi.org/10.1016/j.cmpb.2024.108294Highlights- Brain-computer interface technology uses deep neural networks to improve performance.
- Complex models require extensive data, so many studies try to utilize group data.
- Due to individual variability, simply pooled group data lacks ...
Recent advancements in brain-computer interface (BCI) technology have seen a significant shift towards incorporating complex decoding models such as deep neural networks (DNNs) to enhance performance. These models are ...
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