RATIONALE AND OBJECTIVES: Detection and diagnosis of architectural distortion (AD) on digital breast tomosynthesis (DBT) is challenging. This study applied artificial intelligence (AI) using deep learning (DL) algorithms to detect AD, followed by rad...
BACKGROUND: This study aimed to construct and assess a comprehensive model that integrates MRI-derived deep learning radiomics, functional imaging (fMRI), and clinical indicators to predict early efficacy of radiotherapy in nasopharyngeal carcinoma (...
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Nov 3, 2024
Metabolites serve as vital biomarkers, reflecting physiological and pathological states and offering insights into disease progression and early detection. This study introduces an advanced analytical technique integrating label-free Surface-Enhanced...
RATIONALE AND OBJECTIVES: To establish a multimodal deep learning nomogram for predicting clinically significant prostate cancer in patients with gray-zone PSA levels.
PURPOSE: Osteoporosis, affecting over 200 million individuals, often remains unrecognized and untreated, increasing the risk of fractures in older adults. Osteoporosis is typically diagnosed with bone mineral density (BMD) measured by dual-energy X-r...
International journal of molecular sciences
Nov 3, 2024
Existing deep learning methods have shown outstanding performance in predicting drug-target interactions. However, they still have limitations: (1) the over-reliance on locally extracted features by some single encoders, with insufficient considerati...
International journal of molecular sciences
Nov 3, 2024
The rapid growth of biomedical literature makes it challenging for researchers to stay current. Integrating knowledge from various sources is crucial for studying complex biological systems. Traditional text-mining methods often have limited accuracy...
Human interaction recognition (HIR) between two people in videos is a critical field in computer vision and pattern recognition, aimed at identifying and understanding human interaction and actions for applications such as healthcare, surveillance, a...
The early and highly accurate prediction of COVID-19 based on medical images can speed up the diagnostic process and thereby mitigate disease spread; therefore, developing AI-based models is an inevitable endeavor. The presented work, to our knowledg...
Neural networks : the official journal of the International Neural Network Society
Nov 2, 2024
Deep learning solutions have rapidly emerged for EEG decoding, achieving state-of-the-art performance on a variety of decoding tasks. Despite their high performance, existing solutions do not fully address the challenge posed by the introduction of m...
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