Method and system for constructing oral cancer neck lymphatic metastasis diagnosis algorithm
A diagnostic algorithm and lymphatic metastasis technology, which is applied in the field of construction of oral cancer cervical lymphatic metastasis diagnostic algorithm, can solve problems such as unclear deep learning models, achieve the effect of reducing heavy workload and improving accuracy and efficiency
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no. 1 example
[0046]SeeFigure 1-4 .
[0047]Such asfigure 1 As shown, the present embodiment provides a method of constructing a lymphatic transfer diagnostic algorithm of oral cancer neck, at least the steps of:
[0048]S1, screening the standard oral cancer patients in accordance with preset inclusion and exclude standards, and collect MRI video data, clinical pathological information and follow-up information compliant with standard oral cancer patients.
[0049]Specifically, for step S1, the screeing of the research object is carried out in accordance with the inclusion and exclude standard, the clinical pathological information of the study, MRI image data and follow-up information is collected; the clinical pathological information includes: name, hospitalization, gender, age, diagnosis , Primary / recurrence, neck past history, historical history, radiotherapy history, have cervical, systemic disease, TNM stage, clinical examination, pathological diagnosis, multiple admission history; MRI image inf...
no. 2 example
[0116]SeeFigure 5 .
[0117]Such asFigure 5 As shown, the present embodiment provides a construction system for a lymphatic transfer diagnostic algorithm of oral cancer neck, including:
[0118]The data acquisition module 100 is used to screen for patients with standard oral cancer in accordance with preset inclusion and exclude standards, and collect MRI video data, clinical pathological information and follow-up information that meet the standard oral cancer patients.
[0119]Specifically, for the data acquisition module 100, a screening of research objects is collected in accordance with the inclusion and exclusion criteria, and the clinical pathological information of the study is collected, MRI image data and follow-up information; where clinical pathological information includes: name, hospitalization, gender, age , Diagnosis, primary / recurrence, neck past history, history of tumor disease, radiotherapy history, has cervical, systemic disease, TNM stage, clinical examination, patholo...
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