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A survey on artificial intelligence approaches for medical image classification

机译：医学图像分类人工智能方法调查

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S.N. Deepa;
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年度 2011
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1. A Survey on Artificial Intelligence Approaches for Medical Image Classification [J] . S. N. Deepa, B. Aruna Devi Indian Journal of Science and Technology . 2011,第11期

机译：用于医学图像分类的人工智能方法综述
2. Medical image classification based on artificial intelligence approaches: A practical study on normal and abnormal confocal corneal images [J] . Sharif M. S., Qahwaji R., Ipson S., Applied Soft Computing . 2015,第Null期

机译：基于人工智能方法的医学图像分类：正常和异常共焦角膜图像的实践研究
3. Systematic review of artificial intelligence techniques in the detection and classification of COVID-19 medical images in terms of evaluation and benchmarking: Taxonomy analysis, challenges, future solutions and methodological aspects [J] . O.S. Albahri, A.A. Zaidan, A.S. Albahri, Journal of infection and public health. . 2020,第10期

机译：在评估和基准中的Covid-19医学图像检测和分类中的系统审查：分类分析，挑战，未来解决方案和方法方面
4. Approaches of artificial intelligence in biomedical image processing: A leading tool between computer vision biological vision [C] . Shruti Shukla, Ashish Lakhmani, Ambuj Kumar Agarwal International Conference on Advances in Computing, Communication and Automation . 2016

机译：生物医学图像处理中的人工智能方法：计算机视觉与生物视觉之间的领先工具
5. Investigation of Deep Learning in Medical Imaging for Enhanced Workflow, Improved Diagnosis, and Explanatory Artificial Intelligence [D] . ?Crosby, Jennie Sandoz Marie 2020

机译：增强工作流程，改进诊断和解释性人工智能的医学成像深度学习调查
6. Artificial intelligence for classifying uncertain images by humans in determining choroidal vascular running pattern and comparisons with automated classification between artificial intelligence [O] . Shozo Sonoda, Hideki Shiihara, Hiroto Terasaki, 2021

机译：人工智能对人工血管运行模式和人工智能自动分类进行分类
7. Medical image classification based on artificial intelligence approaches: A practical study on normal and abnormal confocal corneal images [O] . Qahwaji Rami S.R., Ipson Stanley S., Sharif Mhd Saeed, 2015

机译：基于人工智能方法的医学图像分类：正常和异常共焦角膜图像的实践研究

A survey on artificial intelligence approaches for medical image classification

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