Artificial intelligence-based image classification methods for diagnosis of skin cancer: Challenges and opportunities.
Artificial intelligence-based image classification methods for diagnosis of skin cancer: Challenges and opportunities.
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DOI：
10.1016/j.compbiomed.2020.104065
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发表时间：
2020-12
影响因子：
7.7
通讯作者：
Hassanpour S
中科院分区：
文献类型：
--
作者：
Goyal M;Knackstedt T;Yan S;Hassanpour S
最近，人们对开发用于诊断皮肤癌的人工智能（AI）计算机辅助诊断解决方案产生了浓厚的兴趣。随着皮肤癌发病率的不断上升、不断增长的人口的认识较低以及缺乏足够的临床专业知识和服务，迫切需要人工智能系统来协助该领域的临床医生。大量的皮肤病变数据集是公开的，研究人员开发了人工智能解决方案，特别是深度学习算法，以在不同的图像模式（例如皮肤镜、临床和组织病理学图像）中区分恶性皮肤病变和良性病变。尽管人工智能系统在不同皮肤病变的分类方面比皮肤科医生具有更高的准确性，但这些人工智能系统在准备帮助临床医生诊断皮肤癌方面仍处于临床应用的早期阶段。在这篇综述中，我们讨论了用于诊断皮肤癌的基于数字图像的人工智能解决方案的进展，以及改进这些人工智能系统以支持皮肤科医生并提高他们诊断皮肤癌的能力的一些挑战和未来机遇。
Recently, there has been great interest in developing Artificial Intelligence (AI) enabled computer-aided diagnostics solutions for the diagnosis of skin cancer. With the increasing incidence of skin cancers, low awareness among a growing population, and a lack of adequate clinical expertise and services, there is an immediate need for AI systems to assist clinicians in this domain. A large number of skin lesion datasets are available publicly, and researchers have developed AI solutions, particularly deep learning algorithms, to distinguish malignant skin lesions from benign lesions in different image modalities such as dermoscopic, clinical, and histopathology images. Despite the various claims of AI systems achieving higher accuracy than dermatologists in the classification of different skin lesions, these AI systems are still in the very early stages of clinical application in terms of being ready to aid clinicians in the diagnosis of skin cancers. In this review, we discuss advancements in the digital image-based AI solutions for the diagnosis of skin cancer, along with some challenges and future opportunities to improve these AI systems to support dermatologists and enhance their ability to diagnose skin cancer.
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