癌症
癌症医学
深度学习
纳米医学
精密医学
转化式学习
背景(考古学)
人工智能应用
纳米技术
医学
人工智能
机器学习
材料科学
计算机科学
内科学
心理学
病理
古生物学
教育学
纳米颗粒
生物
作者
Junhao Wang,Guan Liu,Cheng Zhou,Xinyuan Cui,Wei Wang,Jiulin Wang,Yixin Huang,Jinlei Jiang,Zhitao Wang,Zengyi Tang,Amin Zhang,Daxiang Cui
出处
期刊:Nanoscale
[The Royal Society of Chemistry]
日期:2024-01-01
卷期号:16 (30): 14213-14246
摘要
Cancer is a major health concern due to its high incidence and mortality rates. Advances in cancer research, particularly in artificial intelligence (AI) and deep learning, have shown significant progress. The swift evolution of AI in healthcare, especially in tools like computer-aided diagnosis, has the potential to revolutionize early cancer detection. This technology offers improved speed, accuracy, and sensitivity, bringing a transformative impact on cancer diagnosis, treatment, and management. This paper provides a concise overview of the application of artificial intelligence in the realms of medicine and nanomedicine, with a specific emphasis on the significance and challenges associated with cancer diagnosis. It explores the pivotal role of AI in cancer diagnosis, leveraging structured, unstructured, and multimodal fusion data. Additionally, the article delves into the applications of AI in nanomedicine sensors and nano-oncology drugs. The fundamentals of deep learning and convolutional neural networks are clarified, underscoring their relevance to AI-driven cancer diagnosis. A comparative analysis is presented, highlighting the accuracy and efficiency of traditional methods juxtaposed with AI-based approaches. The discussion not only assesses the current state of AI in cancer diagnosis but also delves into the challenges faced by AI in this context. Furthermore, the article envisions the future development direction and potential application of artificial intelligence in cancer diagnosis, offering a hopeful prospect for enhanced cancer detection and improved patient prognosis.
科研通智能强力驱动
Strongly Powered by AbleSci AI