Intelligent medical detection and diagnosis assisted by deep learning

Jingxiao Tian, Hanzhe Li, Yaqian Qi, Xiangxiang Wang, Yuan Feng
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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.
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深度学习辅助下的智能医疗检测和诊断
人工智能(AI)与医疗保健的结合促进了智能辅助诊断系统的发展,增强了各个医疗领域的诊断能力。这些人工智能辅助系统利用深度学习算法,帮助医护人员进行疾病筛查、病灶定位和治疗方案选择。随着政策强调医疗人工智能技术的创新,尤其是在中国,人工智能辅助诊断系统已成为提高诊断准确性和效率的重要工具。这些系统分为图像辅助和文本辅助两种模式,利用医学影像数据和临床诊断记录提供诊断支持。在肺癌诊断和治疗方面,人工智能辅助综合解决方案在早期检测和治疗决策支持方面大有可为,尤其是在肺结节的检测方面。总之,人工智能与医疗保健的整合在提高诊断准确性、效率和患者预后方面具有巨大潜力,有助于推动医疗实践的进步。
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