Journal of magnetic resonance imaging : JMRI
Sep 1, 2025
BACKGROUND: Deep learning (DL) models for accurate renal tumor characterization may benefit from multi-center datasets for improved generalizability; however, data-sharing constraints necessitate privacy-preserving solutions like federated learning (...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
In the field of healthcare, the acquisition and annotation of medical images present significant challenges, resulting in a scarcity of trainable samples. This data limitation hinders the performance of deep learning models, creating bottlenecks in c...
Interdisciplinary sciences, computational life sciences
Sep 1, 2025
In top-down proteomics, the accurate identification and characterization of proteoform through mass spectrometry represents a critical objective. As a result, achieving accuracy in identification results is essential. Multiple primary structure alter...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
Deep learning models are vulnerable to adversarial attacks. Transfer-based adversarial examples are crafted against surrogate models and transferred to victim models. However, under the black-box settings, most adversaries have poor transferability o...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
Whole slide pathological images have shown significant potential for patient prognostication. Graph representation learning provides a robust framework for in-depth analysis of whole-slide images to construct predictive models. In this study, we intr...
OBJECTIVES: This study aims to evaluate the feasibility and effectiveness of deep learning-based super-resolution techniques to reduce scan time while preserving image quality in high-resolution prostate diffusion-weighted imaging (DWI) with readout-...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
Ensemble techniques are frequently encountered in machine learning and engineering problems since the method combines different models and produces an optimal predictive solution. The ensemble concept can be adapted to deep learning models to provide...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
In the field of real-time stereo matching, a concise and informative cost volume is crucial for achieving high efficiency and accuracy. To this end, in this paper, we propose the Tri-Fusion Volume (TFV) to effectively fuse both texture details and si...
PURPOSE: To develop a multiparametric breast MRI radiomics and deep learning-based multimodal model for predicting preoperative Ki-67 expression status in breast cancer, with the potential to advance individualized treatment and precision medicine fo...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
In the past decade gradient-based deep learning has revolutionized several applications. However, this rapid advancement has highlighted the need for a deeper theoretical understanding of its limitations. Research has shown that, in many practical le...
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