AI in cancer detection
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Scope of this subject
This cluster of papers focuses on the application of deep learning and machine learning techniques in medical image analysis, particularly in the context of histopathology images, digital pathology, and computer-aided detection for breast cancer diagnosis. The use of convolutional neural networks and whole slide imaging is prominent in these studies, aiming to improve accuracy and efficiency in cancer prognosis and prediction.
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Research vocabulary
computer-aided diagnosis; whole slide images; digital pathology; breast cancer detection; computer-aided detection; histopathological images; histopathological image classification; H&E staining; lung cancer detection; histopathology image analysis; lung nodule detection; breast cancer classification; CT images; computational pathology; whole slide imaging; nuclei segmentation; multiple instance learning; lung nodule classification; lung cancer classification; LIDC-IDRI; microcalcification detection; BreakHis dataset; mammogram classification; breast lesion classification; breast mass detection
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Numeric address and provenance
Morton address: 36174758408260819 · morton4x16-v1
Coordinates: (3, 17, 1702, 10862). The address interleaves categorical identifier bits. Nearby addresses are not guaranteed to describe semantically similar subjects.
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