Prognosis prediction system and method for lung cancer patients

A technology for predicting systems and lung cancer, applied in the field of neural networks, can solve problems that need to be developed

Pending Publication Date: 2020-07-03
SHANGHAI PULMONARY HOSPITAL
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Problems solved by technology

In order to find more visual features in pathological slices, there is evidence to support the feasibility of using convolutional neural networks to evaluate the prognosis of various malignant tumors. The product neural network algorit

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  • Prognosis prediction system and method for lung cancer patients
  • Prognosis prediction system and method for lung cancer patients

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Embodiment Construction

[0038] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0039] It should be noted that, in the case of no conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other.

[0040] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, but not as a limitation of the present invention.

[0041] In order to solve the above problems, the present invention proposes a prognosis prediction system for pa...

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Abstract

The invention discloses a prognosis prediction system and method for lung cancer patients, belonging to the field of neural networks. The system comprises: an annotation module for annotating digitalpathological images to obtain annotated images; an acquisition module for acquiring prognosis data and survival time corresponding to the annotated images; a collection module for respectively addingeach annotated image, the prognosis data and the survival time into a data set to generate training data sets; a classification module for dividing the training data sets into a training set and a test set; a training module for training the training set to obtain a prognosis prediction model for lung cancer patients; a test module for inputting the test set into the prognosis prediction model forthe lung cancer patients to obtain corresponding prediction accuracy; and a prediction module for inputting the digital pathological image of a patient to be detected into the prognosis prediction model for the lung cancer patients to obtain predicted prognosis data and predicted survival time. The prognosis prediction system and method have the following beneficial effect: a doctor can formulatea treatment scheme according to prediction results, so treatment effect is improved, and survival time is prolonged.

Description

technical field [0001] The invention relates to the field of neural networks, in particular to a system and method for predicting the prognosis of lung cancer patients. Background technique [0002] The latest cancer epidemiological statistics in China show that there were 730,000 new lung cancer patients and 600,000 deaths in 2015. Lung cancer has become the cancer with the highest incidence and mortality in China. Lung cancer deaths account for 25% of all cancer deaths. Due to the high recurrence risk and low survival rate of lung cancer, most patients with stage IB-IIIA lung cancer will receive postoperative adjuvant chemotherapy. However, based on parameters such as the degree of residual lesions, lymph node metastasis, and cancer stage, even with the same treatment plan, the overall prognosis of patients will be very different. In recent years, clinicians have been working to find independent prognostic factors related to lung cancer. Tumor size and pathological grad...

Claims

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Application Information

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IPC IPC(8): G16H50/50G06T7/00G06N3/04
CPCG16H50/50G06T7/0012G06T2207/20081G06T2207/30096G06T2207/30061G06N3/045
Inventor 邓家骏陈昶谢冬佘云浪吴俊琪
Owner SHANGHAI PULMONARY HOSPITAL
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