BMC medical informatics and decision making
May 30, 2025
PURPOSE: This study aims to develop a deep learning framework that leverages modality imputation and subregion segmentation to improve grading accuracy in high-grade gliomas.
Cardiovascular disease (CVD) is one of the severe disorders that requires effectual solutions. CVD mainly affects heart functionality in the human body. The impacts of heart disorders are hazardous, which primarily spread from arrhythmia and higher h...
Breast cancer diagnosis remains a crucial challenge in medical research, necessitating accurate and automated detection methods. This study introduces an advanced deep learning framework for histopathological image classification, integrating AlexNet...
Nanotechnology and information communication technology (ICT) are being combined to develop innovative drug delivery systems for targeted sites, such as tumor cells. The particulate targeted drug delivery (PTDD) system involves drugs containing nanop...
Mitochondria are central to cellular energy production and regulation, with their morphology tightly linked to functional performance. Precise analysis of mitochondrial ultrastructure is crucial for understanding cellular bioenergetics and pathology....
To address inter-frame motion artifacts in ultrasound quantitative high-definition microvasculature imaging (qHDMI), we introduced a novel deep learning-based motion correction technique. This approach enables the derivation of more accurate quantita...
Corneal opacity remains a major global cause of vision impairment. Its severity is typically assessed subjectively by clinicians using slit lamp examinations of the anterior segment. While anterior segment optical coherence tomography (AS-OCT) provid...
Visualizing high-dimensional data is essential for understanding biomedical data and deep learning models. Neighbor embedding methods, such as t-SNE and UMAP, are widely used but can introduce misleading visual artifacts. We find that the manifold le...
Optimal surgical methods require accurate prediction of extraction difficulty and complications. Although various automated methods related to third molar (M3) extraction have been proposed, none fully predict both extraction difficulty and post-extr...
Identifying novel drugs that can interact with target proteins is a highly challenging, time-consuming, and costly task in drug discovery and development. Numerous machine learning-based models have recently been utilized to accelerate the drug disco...
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