Intelligent medical detection and diagnosis assisted by deep learning
Jingxiao Tian, Hanzhe Li, Yaqian Qi, Xiangxiang Wang, Yuan Feng
Abstract
The integration of artificial intelligence (AI) in healthcare has led to the development of intelligent auxiliary diagnosis systems, enhancing diagnostic capabilities across various medical domains. These AI-assisted systems leverage deep learning algorithms to aid healthcare professionals in disease screening, localization of focal areas, and treatment plan selection. With policies emphasizing innovation in medical AI technology, particularly in China, AI-assisted diagnosis systems have emerged as valuable tools in improving diagnostic accuracy and efficiency. These systems, categorized into image-assisted and text-assisted modes, utilize medical imaging data and clinical diagnosis records to provide diagnostic support. In the context of lung cancer diagnosis and treatment, AI-assisted integrated solutions show promise in early detection and treatment decision support, particularly in the detection of pulmonary nodules. Overall, the integration of AI in healthcare holds significant potential for improving diagnostic accuracy, efficiency, and patient outcomes, contributing to advancements in medical practice.