The rapid development of deep learning has promoted its application in disease diagnosis, treatment, and prognosis prediction. Medical imaging plays a crucial role in the management of rifampicin-resistant tuberculosis/multidrug-resistant tuberculosi...
Lymphoma histopathological diagnosis is complex due to rare subtypes, morphological overlaps, and poor tumor differentiation. In this paper, an AI-based system using deep transfer learning and simulated federated learning is developed to classify two...
We evaluated the potential utility of imaging parameters derived by normalizing muscle signal intensity on T1-weighted lower leg MRIs in Charcot-Marie-Tooth disease type 1 A (CMT1A) patients, using a deep learning-based automated muscle segmentation ...
Cardiovascular diseases (CVDs) remain a leading global health challenge, necessitating diagnostic solutions that combine high accuracy with clinical interpretability and reproducibility. Traditional auscultation methods rely extensively on clinician ...
This work intends to explore the effectiveness of a dual-track cultivation model for ideological and political literacy in vocational colleges driven by artificial intelligence deep learning models. This work compares the performance of different mod...
Knee abnormalities, such as meniscus tears and ligament injuries, are common in clinical practice and pose significant diagnostic challenges. While traditional imaging techniques-X-ray, Computed Tomography (CT) scan, and Magnetic Resonance Imaging (M...
Understanding the psychological effects of martial arts training requires models that can bridge the gap between observable physical behavior and subjective cognitive states. This study proposes a deep learning framework that explicitly uses question...
Diabetic Retinopathy (DR) remains a leading cause of vision loss globally, necessitating accurate and scalable diagnostic solutions. Existing Deep Learning (DL) models often underutilize lesion-specific cues that are critical for early DR grading, wh...
Deep learning (DL) methods are increasingly applied to address the low signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of low-field MRI (LFMRI). This study evaluates the potential of diffusion models for LFMRI enhancement, comparing the...
BACKGROUND: Sub-Saharan Africa (SSA) bears the highest global burden of under-5 mortality, with congenital heart disease (CHD) as a major contributor. Despite advancements in high-income countries, CHD-related mortality in SSA remains largely unchang...
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