机器学习在缺血性卒中诊治中的应用与展望
Application and prospect of machine learning in the diagnosis and treatment of ischemic stroke
徐瑾妍 1陆浩轩 1谢燕青 1计礼丽 1何文明1
作者信息
- 1. 宁波大学附属第一医院,浙江 宁波 315020
- 折叠
摘要
缺血性卒中有高死亡率、高致残率和高复发率的特点,临床上常出现漏诊、误诊现象.而基于机器学习的计算机辅助技术能够通过对医学文本、影像等资料的特征挖掘,辅助医生快速、准确地提高诊疗效率.本文通过梳理机器学习的不同方法,及其在缺血性卒中预测、诊断、治疗和预后的应用,对未来机器学习在该领域的预测、诊断、制定个性化治疗方案以及医疗资源合理性配置等方面进行展望.
Abstract
Ischemic stroke leads to high mortality,high disability rate,and high recurrence rate.Missed diagnoses and misdiagnoses are common.Computer-assisted technologies based on machine learning,by mining features from medical texts and images are suggested to help doctors improve diagnostic and treatment efficiency quickly and accurately.This review provides an overview of various machine learning methods and research progress in predicting,diagnosing,treating,and prognosis of ischemic stroke.The review is also summarized the future application of machine learning in the field of ischemic stroke for prediction,diagnosis,developing personalized treatment plans,and optimizing medical resource allocation.
关键词
缺血性卒中/人工智能/机器学习/影像诊断/医疗决策Key words
ischemic stroke/artificial intelligence/machine learning/imaging diagnosis/medical decision引用本文复制引用
基金项目
宁波市自然科学基金(2021J240)
宁波市自然科学基金(202003N4231)
浙江省中医药科技计划(2024ZL892)
出版年
2024
NETL
NSTL
万方数据