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- W4322727417 abstract "Colorectal cancer has shown wide spread over a decade, projected number of cancer cases in 2022 will be almost 71% as per ICMR and NCBI data (Kather et al., 100,000 histological images of human colorectal cancer and healthy tissue (Version v0.1) (2018)) due to lifestyle and changing dietary habits. If diagnosis in its early stages, then will significantly boost survival rate of patient. Computer integrated system had positive influence on smoothing out the process of detection or classification. Furthermore, learning methods added more accuracy and details in this process. In this paper, deep learning and transfer learning methods were experimented and analyzed to know the impact of various parameters and model-related factors in identification and classification of malignant cells for colorectal cancer on whole slide stained tissue image samples." @default.
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- W4322727417 date "2023-01-01" @default.
- W4322727417 modified "2023-10-16" @default.
- W4322727417 title "Deep and Transfer Learning in Malignant Cell Classification for Colorectal Cancer" @default.
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- W4322727417 doi "https://doi.org/10.1007/978-981-19-7447-2_29" @default.
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