Bimodal artificial intelligence using TabNet for differentiating spinal cord tumors—Integration of patient background information and images

We proposed a bimodal artificial intelligence that integrates patient information with images to diagnose spinal cord tumors. Our model combines TabNet, a state-of-the-art deep learning model for tabular data for patient information, and a convolutional neural network for images. As training data, w...

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Detalles Bibliográficos
Autores principales: Kita, Kosuke, Fujimori, Takahito, Suzuki, Yuki, Kanie, Yuya, Takenaka, Shota, Kaito, Takashi, Taki, Takuyu, Ukon, Yuichiro, Furuya, Masayuki, Saiwai, Hirokazu, Nakajima, Nozomu, Sugiura, Tsuyoshi, Ishiguro, Hiroyuki, Kamatani, Takashi, Tsukazaki, Hiroyuki, Sakai, Yusuke, Takami, Haruna, Tateiwa, Daisuke, Hashimoto, Kunihiko, Wataya, Tomohiro, Nishigaki, Daiki, Sato, Junya, Hoshiyama, Masaki, Tomiyama, Noriyuki, Okada, Seiji, Kido, Shoji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10520519/
https://www.ncbi.nlm.nih.gov/pubmed/37766987
http://dx.doi.org/10.1016/j.isci.2023.107900

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10520519/
https://www.ncbi.nlm.nih.gov/pubmed/37766987
http://dx.doi.org/10.1016/j.isci.2023.107900

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