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- W4385430905 abstract "AI-based recognition of tumor cell morphology holds great promise in the field of cancer pathology. Tumor cell morphology is a method used to diagnose and evaluate tumors by observing and analyzing their cellular structure and characteristics. Traditionally, tumor cell morphology recognition relies on manual observation and assessment, which can be subjective and prone to human error. The rapid advancement of AI technology offers new possibilities for automating and accurately identifying tumor cell morphology. Through the use of deep learning and computer vision techniques, AI can learn and recognize specific morphological features from large volumes of cytological images. It can automatically detect and classify tumor cells based on characteristics such as nuclear shape, size, and staining properties. This information provides crucial insights for accurate tumor diagnosis, grading, and staging. The advantages of AI in recognizing tumor cell morphology include high accuracy, consistency, and speed. Compared to manual observation, AI can process large amounts of image data and perform analysis in a short period, saving time and human resources. Additionally, AI has the potential to identify subtle morphological changes, which is significant for early cancer diagnosis and prognosis assessment. In summary, the application of AI in recognizing tumor cell morphology provides new tools and approaches for tumor diagnosis and treatment. With ongoing technological advancements and improvements, AI is expected to play a greater role in the field of cancer pathology, enhancing diagnostic accuracy, optimizing treatment strategies, and improving patient outcomes." @default.
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- W4385430905 date "2023-07-01" @default.
- W4385430905 modified "2023-10-14" @default.
- W4385430905 title "Advances in AI‐based Cancer Cytopathology (3/2023)" @default.
- W4385430905 doi "https://doi.org/10.1002/inmd.12048" @default.
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