Supporting data for “Digital Healthcare Technology for Precision Oncology: development of artificial intelligence-driven clinical models to predict prognosis for oral squamous cell carcinoma”
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https://figshare.com/articles/dataset/Supporting_data_for_Digital_Healthcare_Technology_for_Precision_Oncology_development_of_artificial_intelligence-driven_clinical_models_to_predict_prognosis_for_oral_squamous_cell_carcinoma_/25762782
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The data for the thesis consists of separate files for chapters 2, 3, and 4. The Chapter 2, 3, 4 specifically contains different sets of data, including:1. Patient data: patients with oral squamous cell carcinoma from the Queen Mary Hospital (Chapter 2)2. Brightfield vs confocal images: tumor and non-tumor images (Chapter 3)3. Intrarater reliability: tumor images (Chapter 3)4. Waveform analysis: comparisons among early recurrence, late/no recurrence, and non-tumor groups (Chapter 3)5. 512x512 images: brightfield and confocal images in 512x512 pixels from oral cancer patients (Chapter 3)6. Biocompatibility and cell migration: 2.5D cell culture for SCC15 cell line (Chapter 4)7. Colony assay: 2D cell culture for SCC15 cell line (Chapter 4)8. Scanning electron microscopy (Chapter 4)9. Wound healing assay (Chapter 4)
创建时间:
2024-05-21



