Thyroid nodule risk prediction method and system based on big data

A thyroid nodule and risk prediction technology, applied in the field of risk prediction of thyroid nodules based on big data, can solve the problems of inconvenient risk prediction, inconvenient inspection data, and data disorder, and achieve the effect of rapid risk prediction and rapid extraction

Inactive Publication Date: 2018-12-07
THE FIRST AFFILIATED HOSPITAL OF JINAN UNIV
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Problems solved by technology

[0002] Thyroid nodules refer to lumps in the thyroid gland, which can move up and down with the thyroid gland with the swallowing action. Immunity and new organisms can all be manifested as nodules. Thyroid nodules can be single or multiple. The incidence of multiple nodules is higher than that of single nodules, but the incidence of thyroid cancer is higher for single nodules. Thyroid nodules Nodules or lumps, and goiter are the main symptoms. In addition, most patients with thyroid nodules have no clinical symptoms. They can f...

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  • Thyroid nodule risk prediction method and system based on big data
  • Thyroid nodule risk prediction method and system based on big data
  • Thyroid nodule risk prediction method and system based on big data

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Embodiment

[0023] In this embodiment, a method for predicting the risk of thyroid nodules based on big data is proposed, which includes the following steps:

[0024] S1: Clinical data collection: collect the data of the patient's medical history, symptoms and signs, and record the data;

[0025] S2: Ultrasound examination: Perform thyroid ultrasonography on the patient to understand the size, shape, margin, internal structure, echo characteristics, blood flow and neck lymph nodes of the nodule, and record the examination data;

[0026] S3: fine-needle aspiration examination: perform thyroid fine-needle aspiration cytology examination on the patient, and record the data of the examination results;

[0027] S4: Data integration: integrate the data mentioned in S1, S2 and S3, eliminate useless data, and classify and sort the data;

[0028] S5: Risk prediction: compare the integrated data in S4 with the normal data, and make a risk prediction based on the comparison results.

[0029] refer...

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Abstract

The invention discloses a thyroid nodule risk prediction method and system based on big data. The method comprises following steps of S1: acquisition of clinic data: collecting data of medical histories, signs and symptoms of a patient and recording the data; S2: ultrasonic examination: carrying out thyroid nodule checking of the patient, knowing the size, the shape, the nodule edge, the inner structure, the echo features, the blood flow conditions and the cervical lymph node conditions of the nodule; and S3: fine needle aspiration examination: carrying out thyroid nodule fine needle aspiration cytological examination on the patient, checking result data and carrying out recording. According to the invention, by acquiring clinic data of the patient, carrying out the ultrasonic examinationand the fine needle aspiration examination on the patient, and integrating the examination data, rapid extraction of the data is facilitated and risk prediction can be rapidly made.

Description

technical field [0001] The present invention relates to the technical field of thyroid nodule risk prediction, in particular to a method and system for thyroid nodule risk prediction based on big data. Background technique [0002] Thyroid nodules refer to lumps in the thyroid gland, which can move up and down with the thyroid gland with the swallowing action. Immunity and new organisms can all be manifested as nodules. Thyroid nodules can be single or multiple. The incidence of multiple nodules is higher than that of single nodules, but the incidence of thyroid cancer is higher for single nodules. Thyroid nodules Nodules or lumps, and goiter are the main symptoms. In addition, most patients with thyroid nodules have no clinical symptoms. They can find thyroid nodules through self-touch or physical examination, or go to the doctor because of goiter, and perform physical examination or B According to the super imaging examination, the existing risk prediction of thyroid nodu...

Claims

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Application Information

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IPC IPC(8): G16H50/30
CPCG16H50/30
Inventor 张水兴张斌方进张璐莫笑开陈秋颖
Owner THE FIRST AFFILIATED HOSPITAL OF JINAN UNIV
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