Tanja Fehm, Francesco Cottone, Kyle Dunton, Fabrice André, Ian Krop, Yeon Hee Park, Michelino De Laurentiis, Yasuo Miyoshi, Anne Armstrong, Manuel Ruiz Borrego, Rinat Yerushalmi, Francois P Duhoux, Toshimi Takano, Wenjing Lu, Anton Egorov, Sung-Bae Kim
Trastuzumab deruxtecan versus treatment of physician's choice in patients with HER2-positive metastatic breast cancer (DESTINY-Breast02): patient-reported outcomes from a randomised, open-label, multicentre, phase 3 trial
The Lancet. Oncology
species identification analysis methods based deep learning becoming prevalent due datadriven taskoriented nature commonly used convolutional neural network cnn model well applied raman spectra recognition however faced similar molecules functional groups features overlapping peaks weak peaks may fully extracted using cnn model potentially hinder accurate species identification based practical challenges fusion multimodal data effectively meet comprehensive accurate analysis actual samples compared singlemodal data study propose doublebranch cnn model integrating raman image multimodal data named sidbnet addition developed onedimensional convolutional neural network combining dilated convolutions efficient channel attention mechanisms spectral branching effectiveness model demonstrated using gradcam method visualize key regions concerned model compared singlemodal multimodal classification methods sidbnet model achieved superior performance classification accuracy 988 proposed method provided new reference species identification based multimodal data fusion