Method for evaluating thyroid nodules by combining protein mass spectrometry with deep learning

A thyroid nodule and deep learning technology, applied in the field of proteomics, can solve problems such as over-treatment of benign nodules, inconvenience in personal life, and inability to classify nodules

Inactive Publication Date: 2020-06-16
WESTLAKE UNIV
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Problems solved by technology

[0003] The classification of thyroid nodules in clinical medicine mainly depends on the results of cytopathology. Cytopathology is to extract a small part of thyroid tissue through biopsy puncture for cell smear to observe the changes of cell morphology, but there are still some benign and malignant nodules that need to be evaluated. Observe whether the tissue invades the capsule to determine whether it is benign or malignant, that is, 30% of the nodules cannot be classified using the method of cytopathology, which leads to the problem of overtreatment of...

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  • Method for evaluating thyroid nodules by combining protein mass spectrometry with deep learning
  • Method for evaluating thyroid nodules by combining protein mass spectrometry with deep learning
  • Method for evaluating thyroid nodules by combining protein mass spectrometry with deep learning

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[0009] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art belong to the protection scope of the present invention.

[0010] Those skilled in the art should understand that in the disclosure of the present invention, the terms "vertical", "transverse", "upper", "lower", "front", "rear", "left", "right", " The orientations or positional relationships indicated by "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. are based on the orientation or positional relationship shown in the drawings, which are only for the convenience of describing the present invention and The above terms are used to s...

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Abstract

The invention provides a method for evaluating thyroid nodules by combining protein mass spectrometry with deep learning. According to the scheme, a genetic algorithm is adopted to obtain a protein combination capable of reflecting benign and malignant probabilities of thyroid nodules; based on a deep learning model, thyroid nodules are accurately classified by utilizing the selected protein combination; the possibility of malignant nodules is assessed, the surgical treatment cost and the treatment cost generated by subsequent medication can be greatly reduced, and meanwhile, the medical resource waste caused by excessive treatment can be reduced while the life quality of a patient is greatly improved.

Description

technical field [0001] The invention relates to the field of proteomics, in particular to a method for evaluating thyroid nodules by combining proteomics mass spectrometry with deep learning. Background technique [0002] Thyroid nodules refer to lumps in the thyroid gland, which is a common clinical disease and can be caused by a variety of causes. According to the survey, about 50% of the population suffer from thyroid nodules, while only 10% of all thyroid nodules Left and right are malignant nodules. [0003] The classification of thyroid nodules in clinical medicine mainly depends on the results of cytopathology. Cytopathology is to extract a small part of thyroid tissue through biopsy puncture for cell smear to observe the changes of cell morphology, but there are still some benign and malignant nodules that need to be evaluated. Observe whether the tissue invades the capsule to determine whether it is benign or malignant, that is, 30% of the nodules cannot be classif...

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Application Information

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IPC IPC(8): G16B20/00G06N3/04G06N3/08
CPCG16B20/00G06N3/084G06N3/045
Inventor 郭天南戈帕拉克里希纳·艾耶官爱莲李子青孙耀庭臧泽林萨蒂亚穆尔蒂·塞尔瓦拉扬朱怡
Owner WESTLAKE UNIV
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