Named Entity Recognition (NER) plays a crucial role in extracting important information such as treatment methods, symptoms, and herbal prescriptions from Traditional Chinese Medicine (TCM) electronic medical records. However, existing NER methods of...
Male pattern hair loss (MPHL) is a common dermatological condition with significant psychological and clinical impacts. Traditional grading systems, such as the Norwood-Hamilton and Basic and Specific (BASP) classifications, rely on subjective assess...
Accurate survival prediction is essential for guiding follow-up strategies in patients with cT1b renal cell carcinoma (RCC). Traditional AJCC TNM staging systems provide limited prognostic accuracy. Data from the SEER database were used, which includ...
Breast cancer detection and diagnosis remain challenging due to the complexity of tumor tissues and image quality variations, which hinder early and accurate identification. Timely diagnosis is vital for initiating treatment and improving patient out...
Recently, the integration of smartphone-based platforms into biomedical sensing has provided portable, low-cost, and scalable alternatives to conventional laboratory diagnostics. According to the advances in mobile imaging, embedded sensors, microflu...
Analysing cough sounds is vital in pulmonary medicine. Recently, AI tools are being trained to analyse the acoustic signals of cough sounds so that more cases can be quickly tested, thereby reducing the patient load on primary healthcare systems. In ...
Continuous glucose monitoring (CGM) devices allow real-time glucose readings leading to improved glycemic control. However, glucose predictions in the lower (hypoglycemia) and higher (hyperglycemia) extremes, referred as glycemic excursions, remain c...
The nnU-Net framework has played a crucial role in medical image segmentation and has become the gold standard in multitudes of applications targeting different diseases, organs, and modalities. However, so far it has been used primarily in a central...
The accurate classification of skin cancer types is a critical task in medical diagnostics, requiring robust and reliable models to distinguish between various skin lesions. Despite advancements in deep learning, developing models that generalize wel...
Student stress in higher education remains a pervasive problem, yet many institutions lack affordable, scalable, and interpretable tools for its detection and management. Existing methods frequently depend on costly physiological sensors and opaque m...
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