Research progress on deep learning-based computational pathology in prognostic prediction and therapeutic response evaluation of colorectal cancer
10.7683/xxyxyxb.2024.07.002
- VernacularTitle:基于深度学习的计算病理学在结直肠癌预后预测和疗效评估中的研究进展
- Author:
Yizhan LU
1
,
2
;
Xuezhi ZHOU
Author Information
1. 新乡医学院医学工程学院智能医学工程教研室,河南 新乡 453003
2. 河南省神经传感与控制工程研究中心,河南 新乡 453003
- Keywords:
computational pathology;
deep learning;
colorectal cancer;
prognostic prediction;
therapeutic response evaluation
- From:
Journal of Xinxiang Medical College
2024;41(7):609-613
- CountryChina
- Language:Chinese
-
Abstract:
Colorectal cancer is one of the most common malignant tumors and has become a serious threat to people's lives and health.The clinics currently use the tumor-lymph node-metastasis(TNM)staging system as the main reference standard for risk stratification and prognostic prediction in colorectal cancer,but there are still large differences in prognosis between patients with the same pathologic stage.Therefore,there is an urgent need for more accurate prognostic prediction models.Computational pathology is a new field that utilizes computers and artificial intelligence(AI)to analyze histopathological images.AI enables comprehensive and quantitative analysis of histopathological images,which shows significant value and potential in prognostic prediction of colorectal cancer.This article reviews the application of computational pathology in prognostic prediction and therapeutic response evaluation of colorectal cancer,and summarizes the problems of this technique in the prognostic prediction process as well as the future development direction.
