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Unveiling the relation between swallowing muscle mass and skeletal muscle mass in head and neck cancer patients.

Eur Arch Otorhinolaryngol

January 2025

Department of Otorhinolaryngology, Head and Neck Surgery, University Medical Center Groningen, University of Groningen, Hanzeplein 1, PO box 30.001, Groningen, 9700RB, The Netherlands.

Purpose: Sarcopenia, characterized by loss of skeletal muscle mass (SMM) and strength, often leads to dysphagia in the elderly. This condition can also worsen treatment outcomes in head and neck cancer (HNC) patients, who are susceptible to swallowing difficulties. This study aimed to establish the correlation between swallowing muscle mass (SwMM) and SMM in HNC patients.

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Traditional Chinese medicine (TCM) has long utilized tongue diagnosis as a crucial method for assessing internal visceral condition. This study aims to modernize this ancient practice by developing an automated system for analyzing tongue images in relation to the five organs, corresponding to the heart, liver, spleen, lung, and kidney-collectively known as the "five viscera" in TCM. We propose a novel tongue image partitioning algorithm that divides the tongue into four regions associated with these specific organs, according to TCM principles.

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Introduction: Chronic kidney disease (CKD) is a significant global health problem associated with high morbidity and mortality rates. Traditional Chinese Medicine (TCM) utilizes tongue diagnosis to differentiate symptoms and predict prognosis. This study examines the relationship between tongue characteristics and CKD severity using an automatic tongue diagnosis system (ATDS), which captures tongue images non-invasively to provide objective diagnostic information.

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Background And Aims Of The Study: Fluctuations in environmental temperature and humidity significantly affect human physiology and disease manifestation. In the Lingnan region of China, high summer temperatures and humidity often cause symptoms like diminished appetite, sticky tongue coating, sticky stool, unsatisfactory defecation, lethargy, and joint heaviness. These are referred to as "Dampness Syndrome" in Traditional Chinese Medicine (TCM).

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Lightweight YOLOv8 for tongue teeth marks and fissures detection based on C2f_DCNv3.

Sci Rep

January 2025

Key Laboratory of Instrumentation Science, Dynamic Measurement of Ministry of Education, North University of China, Taiyuan, 030051, Shanxi, China.

This paper propose a significantly enhanced YOLOv8 model specifically designed for detecting tongue fissures and teeth marks in Traditional Chinese Medicine (TCM) diagnostic images. By integrating the C2f_DCNv3 module, which incorporates Deformable Convolutions (DCN), replace the original C2f module, enabling the model to exhibit exceptional adaptability to intricate and irregular features, such as fine fissures and teeth marks. Furthermore, the introduction of the Squeeze-and-Excitation (SE) attention mechanism optimizes feature weighting, allowing the model to focus more accurately on key regions of the image, even in the presence of complex backgrounds.

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