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Prognosis survival stage prediction method and system based on machine learning

A prediction method and machine learning technology, applied in the field of data statistics, can solve problems such as the inability to judge survival conditions based on big data, and achieve the effect of high prediction accuracy

Active Publication Date: 2022-05-13
PEKING UNIV SCHOOL OF STOMATOLOGY +1
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Problems solved by technology

[0003] The purpose of the present invention is to provide a method and system for predicting the prognosis and survival stage based on machine learning, so as to at least partially solve the problems existing in the prior art that cannot be made based on big data. Technical Problems in Prognosis and Survival Judgment

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Embodiment Construction

[0036] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0037] The present invention proposes a prediction method of prognosis and survival stage based on machine learning, which can more accurately rank the factors affecting the patient's condition, and perform postoperative survival prediction on the basis of this, so as to standardize and save detailed patient data.

[0038] In a specific embodiment, such as figure 1 As shown, the prognosis survival stage prediction method based on m...

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Abstract

The invention discloses a prognosis survival stage prediction method and system based on machine learning, and the method comprises the steps: obtaining the original information data of a patient in a previous preset time period, and integrating the original information data of the patient, so as to obtain a first data set without recurrence time and a second data set with recurrence time; based on the pre-operation information, the post-operation information and the survival state of each corresponding patient, analyzing to obtain the correlation degree among the pre-operation information, the post-operation information and the survival state; training in the first data set to obtain a postoperative survival probability prediction model; according to the postoperative survival probability model, it is judged that the survival probability of the target patient is smaller than or equal to a preset value, and a survival time period prediction model is obtained through training in the second data set. The technical problem that prognosis survival condition judgment cannot be made based on big data is solved.

Description

technical field [0001] The present invention relates to the technical field of data statistics, in particular to a method and system for predicting prognosis and survival stages based on machine learning. Background technique [0002] At present, surgery, radiotherapy, chemotherapy, and biological therapy are the four major means of treating cancer. Taking the treatment of salivary gland cancer as an example, comprehensive sequential treatment is currently advocated for the treatment of salivary gland cancer, that is, according to the specific situation of the patient, a variety of treatment methods are adopted in a planned and step-by-step manner in order to achieve the best therapeutic effect. However, before the implementation of medical methods, it is currently impossible to combine big data to give a basic judgment on prognosis and survival, and it is impossible to provide doctors and patients with a more accurate prediction of prognosis. Moreover, the existing technol...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H70/60G16H50/70G16H50/30G16H10/60G06N5/00
CPCG16H70/60G16H10/60G16H50/30G16H50/70G06N5/01
Inventor 彭歆王海辉贾梦琪王学超高敏俞光岩章文博杜文于尧叶鹏
Owner PEKING UNIV SCHOOL OF STOMATOLOGY
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