开放获取期刊获得更多读者和引用
700 种期刊 和 15,000,000 名读者 每份期刊 获得 25,000 多名读者
Lucas Pedro
To explore a new artificial intelligence (AI)-aided method to assist the clinical diagnosis of femoral intertrochanteric fracture (FIF), and further compare the performance with human level to confirm the effect and feasibility of the AI algorithm. In the realm of healthcare, the integration of artificial intelligence (AI) has heralded a transformative era of intelligent medical practices. This paper delves into the application of AI technology in the detection of femoral intertrochanteric fractures. Through advanced algorithms and deep learning, AI systems demonstrate a remarkable ability to enhance the accuracy and efficiency of fracture diagnosis. This research explores the potential of AI-powered detection methods, their implications for patient care, and the broader implications for the future of intelligent healthcare.