Sensory stimulation of the brain reverberates in its recurrent neural networks. However, current computational models of brain activity do not separate immediate sensory responses from this intrinsic dynamic. We apply a vector-autoregressive model wi...
BACKGROUND: Inflammatory bowel disease (IBD) is a chronic autoimmune disorder with an increasing prevalence in the general population. Internet-based communities have become vital for communication among patients with IBD, especially throughout the C...
BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is a prevalent respiratory condition often accompanied by depression, which exacerbates disease burden and impairs quality of life. Early identification of depression risk in COPD patients rema...
This study developed a deep learning model for the automated detection and classification of impacted third molars using the Pell and Gregory Classification, Winter's Classification, and Pederson Difficulty Index. Panoramic radiographs of patients tr...
Deep neural networks (DNNs) excel at extracting insights from complex data across various fields, however, their application in cognitive neuroscience remains limited, largely due to the lack of approaches with interpretability. Here, we employ two d...
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Jul 2, 2025
Breast cancer remains a global health challenge, with an increasing number of cases necessitating innovative approaches to streamline patient management prior to treatment. In this study, we present a comprehensive aptamer-involved surface-enhanced R...
OBJECTIVE: To investigate the effect of manual acupuncture manipulations (MAMs) on subcutaneous muscle tissue, by developing quantitative models of "lifting and thrusting" and "twisting and rotating", based on machine learning techniques.
OBJECTIVES: To develop a multidimensional clinical indicator-based prediction model for identifying high-risk patients with fertilization failure conventional in vitro fertilization (c-IVF) cycles, thereby optimizing therapeutic decision-making.
DNA methylation in breast tumours has been extensively studied and has provided valuable insights into the clinical heterogeneity of breast cancer. In this review, we summarise the current literature that has used DNA methylation markers to subtype b...
BACKGROUND: The healthcare sector is undergoing a digital transformation, where the integration of Artificial Intelligence (AI) plays a vital role in reshaping healthcare practices. AI technologies promise to improve work procedures, mitigate future ...
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