ArticleMethods in molecular biology (Clifton, N.J.)2025
MLCDL: A Critical Practice and Implementation of Multi-tissue Classification and Diagnosis Using Deep Learning Algorithm.
Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
Traditional machine learning methods have been replaced by deep learning (DL), a modern, cutting-edge approach to classifying textures and localizing tissues. This study introduces a dataset for texture classification at the image level using integrated transfer learning-based EfficientNet-B7 deep convolutional neural networks (CNN). The dataset comprised 381 images of dimensions 150 × 150 pixels for training, validation, and testing. The model attained an accuracy of 89.33%, 52.43%, and, 51.326% for training, validation, and testing datasets while training losses are 0.2513, 1.846, and 1.6137, respectively. The straightforwardness of the framework, setup, and execution also plays a role in the findings of this research. Moreover, these proposed techniques can suggest extracting more prognostic information than an experienced human observer.
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