Chatbot Combined with Deep Convolutional Neural Network for Skin Cancer Detection
- 10.2991/978-94-6463-040-4_7How to use a DOI?
- Convolutional Neural Network; Chatbot; Skin Cancer Detection; NLP
For the sake of raising people's serious awareness of skin cancer and providing a convenient way to diagnose skin cancer, this study designs an application to help users figure out the true situation of their skin. In this field, many current studies still cannot achieve high accuracy for skin cancer detection. To increase the accuracy of the previous models from others, firstly, this study trains the proposed model by numbers converted by RGB using a 10k jpg file. Then, the deep convolutional neural network was applied with three units: a 2D convolutional unit to convolute the kernel with all the data in its receptive field, a pooling unit to decrease the dimension of the input, and a dense unit to generalize traits from the data. In addition, since it is noticed that the application that gives feedback on the diagnosis is missing, this paper set up a chatbot based on natural language processing and decides what functions shall the proposed bot provide. The developed application can diagnose seven kinds of skin symptoms related to skin cancer and give out some basic information and advice based on the result. Finally, the results indicated that the model achieves higher accuracy and makes the interaction with the user becomes true.
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Cite this article
TY - CONF AU - Qianfei Hu AU - Haochong Xia AU - Tianrui Zhang PY - 2022 DA - 2022/12/27 TI - Chatbot Combined with Deep Convolutional Neural Network for Skin Cancer Detection BT - Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022) PB - Atlantis Press SP - 35 EP - 41 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-040-4_7 DO - 10.2991/978-94-6463-040-4_7 ID - Hu2022 ER -