Accurate assessment of thyroid cartilage invasion is crucial for treatment decision-making and prognosis evaluation in laryngeal squamous cell carcinoma (LSCC). This study aimed to compare the performance of the radiomics and deep learning (DL) model...
Data scarcity remains a major obstacle to the application of deep learning techniques in medical imaging, particularly for rare neurodegenerative diseases. This study investigates the use of denoising diffusion probabilistic models (DDPMs) to generat...
Journal of chemical information and modeling
Nov 14, 2025
Topological data analysis (TDA) has emerged as a powerful framework for extracting robust, multiscale, and interpretable features from complex molecular data for artificial intelligence (AI) modeling and topological deep learning (TDL). This review p...
Understanding the intricate relationship between brain structure and function is a cornerstone challenge in neuroscience, critical for deciphering the mechanisms that underlie healthy and pathological brain function. In this work, we present a compre...
Task-based functional magnetic resonance imaging (fMRI) reveals individual differences in neural correlates of cognition but faces scalability challenges due to cognitive demands, protocol variability, and limited task coverage in large datasets. Her...
Revealing new lncRNA-disease associations (LDAs) is necessary to decipher pathological mechanisms and find new clues of diagnosis and therapy for complex diseases. However, experimental methods for LDA identification need a significant amount of time...
High-throughput analysis of EEG data has significantly contributed to understanding neural dynamics in Alzheimer's disease diagnosis. However, the complexity and high dimensionality of EEG signals pose challenges for traditional classification method...
Pneumonia remains a significant global health threat, especially among children, the elderly, and immunocompromised individuals. Chest X-ray (CXR) imaging is commonly used for diagnosis, but manual interpretation is prone to errors and variability. T...
Online adaptation in magnetic resonance imaging-guided radiotherapy (MRgRT) for lung cancer is hindered by time-consuming organs-at-risk (OARs) recontouring on daily MR images (dMRIs) and inter-/intra-observer variability. Deep learning auto-segmenta...
The proliferation of deepfakes is a major threat to the believability of online media and the stability of public discourse. These hyper-realistic fake videos, nearly indistinguishable from genuine content, can be misused to spread disinformation, co...
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