Pomegranate cultivation faces significant challenges due to fruit diseases that significantly impact crop yield and farmer income. Traditional methods for disease detection are often slow and prone to errors, delaying timely intervention. This paper ...
To develop our proposed technology method to improve retinal pigment epithelium (RPE) detection in optical coherence tomography (OCT) images and compare its efficacy with Topcon's automated segmentation algorithm across multiple retinal diseases and ...
Automatic and reliable urine sediment analysis is essential for timely diagnosis and management of renal and urinary disorders. However, manual methods are time-consuming, subjective, and limited by operator abilities. In this study, we propose a nov...
The combination of sports psychology and new wearable technology is allowing experts to assess psychological and cognitive performance in elite basketball more accurately. This study investigates the application of Human Activity Recognition (HAR) us...
Named Entity Recognition (NER) stands as a fundamental task in Chinese information processing. However, it encounters unique difficulties due to the lack of explicit word boundaries in the Chinese language. This study proposes framing Chinese NER as ...
Prediabetes is a major risk factor for the development of diabetes, defined by blood glucose levels that are elevated but not yet high enough to meet the diagnostic criteria for Diabetes Mellitus. This condition is often clinically "silent" yet it ca...
Acute Rheumatic Fever and Rheumatic Heart Disease (ARF/RHD) affect over 45 million people globally. ARF/RHD are autoimmune complications following group A streptococcal infections. Current diagnosis of ARF requires thorough medical examination, echoc...
This research focuses on enhancing the extraction efficiency of Phylloporia ribis and assessing its biological functions. Key parameters including extraction temperature, duration, and ethanol-to-water ratio were optimized through both Response Surfa...
ccRCC is an aggressive, heterogeneous tumor with a poor prognosis. Prognostic assessments need multi-modal data. Radiological images have limits, while pathological images offer micro-level details. Integrating these for ccRCC outcome prediction is i...
The segmentation accuracy of deep learning-based brain tumor MRI images still requires further improvement. We proposed a conditional diffusion network that incorporates image information into the mask's perturbed diffusion process. By optimizing the...
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