OBJECTIVES: Falls are among the most prevalent workplace accidents, necessitating thorough screening for susceptibility to falls and customization of individualized fall prevention programs. The aim of this study was to develop and validate a high fa...
To address the challenges of innovation and efficiency in film choreography, this study proposes a dance generation model based on the generative adversarial networks. The model is trained using the AIST++ dance motion dataset, incorporating data fro...
Identifying anatomical landmarks in endoscopic video frames is essential for the early diagnosis of gastrointestinal diseases. However, this task remains challenging due to variability in visual characteristics across different regions and the limite...
Boxing punch type classification and kinematic analysis are essential for coaches and athletes, providing critical insights into punch variety and effectiveness, which are vital for performance improvement. Existing methods for punch recognition and ...
Technology and health care : official journal of the European Society for Engineering and Medicine
Jan 1, 2025
BACKGROUND: Deep learning has demonstrated superior performance over traditional methods for the estimation of heart rates in controlled contexts. However, in less controlled scenarios this performance seems to vary based on the training dataset and ...
BACKGROUND: Radical gastrectomy with D2 lymphadenectomy is standard surgical protocol for locally advanced gastric cancer. The surgical experience and skill in recognizing blood vessels and performing lymph node dissection differ between surgeons, wh...
The use of artificial intelligence (AI) in medicine is rising fast. We continually hear about novel AI-based technologies being deployed to aid clinical teams in areas like interpreting medical images, understanding pathology, determining diagnosis, ...
BACKGROUND: Near-infrared indocyanine green angiography allows experienced surgeons to reliably evaluate parathyroid gland vitality during thyroid and parathyroid operations in order to predict postoperative function. To facilitate equal performance ...
PURPOSE: The purpose of this study was to develop deep learning models for surgical video analysis, capable of identifying minimally invasive glaucoma surgery (MIGS) and locating the trabecular meshwork (TM).
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