Tumor pre-diagnosis information processing system and method

Abstract

The invention belongs to the technical field of clinical data processing and discloses a tumor pre-diagnosis information processing system and method. The tumor pre-diagnosis information processing system includes an appointment module, a data recording module, a central control module, a doctor allocation module, an online diagnosis module, a tumor part distinguishing module, a tumor prediction module, a consulting module, a system maintenance module, a data storage module and a display module. The influences of fluorescence of autofluorescence substances can be removed through the tumor partdistinguishing module, and compared with previous conditions, the system can accurately distinguish tumor parts. Meanwhile, a database is built through the tumor prediction module according to historical tumor data of different kinds of patients suffering from malignant tumors, a proportion risk function is thus set, and the data of tested persons is converted and completed with missing values; then, the completed data is substituted into the proportion risk function, a tumor prediction model is established, tumor prediction can be conducted accurately, and the use demands of users are met.

Description

technical field [0001] The invention belongs to the technical field of clinical data processing, and in particular relates to a tumor prediagnosis information processing system and method. Background technique [0002] Tumor refers to the neogrowth formed by the proliferation of local tissue cells in the body under the action of various tumorigenic factors, because this neogrowth is mostly in the form of space-occupying blocky protrusions, also known as neoplasm (neoplasm) . According to the cell characteristics of new organisms and the degree of harm to the body, tumors are divided into two categories: benign tumors and malignant tumors, and cancer is the general term for malignant tumors. It should be noted that cancer and cancer are two different concepts. Cancer refers to epithelial malignant tumors. For example, malignant tumors formed by the intestinal mucosal epithelium are called colonic mucosal epithelial carcinoma, or colorectal cancer for short. Formed by the sk...

AI Technical Summary

Problems solved by technology

[0004] (1) The disease appointment system currently in use is not clear enough about the appointment status of the disease, and the classification lines are thick, resulting in a large number of people making appointments at the same window, and a lot of time is wasted in the process of patients waiting for diagnosis according to the appointment. Diagnosis and appointment When the conditions are not met, you need to wait again, which is less efficient

[0005] (2) The current tumor pre-diagnosis information processing system has poor accuracy in judging the tumor location; at the same time, it cannot predict the tumor disease before it occurs. Doctors are deployed, the deployment efficiency is low, and it is easy to delay the treatment

[0006] (3) When storing data, it is necessary to classify a large amount of data. The traditional data classification method is slow, and different data needs to be stored again with different programming. The storage type is easy to confuse and the processing is slow.

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