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作 者:谈冰冰 高国伟 TAN Bingbing;GAO Guowei(Beijing Key Laboratory of Sensors,Beijing Information Science and Technology University,Beijing 100101,China;Key Laboratory of Modern Measurement and Control Technology,Ministry of Education,Beijing Information Science and Technology University,Beijing 100192,China)
机构地区:[1]北京信息科技大学传感器北京市重点实验室,北京100101 [2]北京信息科技大学现代测控技术教育部重点实验室,北京100192
出 处:《智能计算机与应用》2023年第12期149-153,157,共6页Intelligent Computer and Applications
基 金:国家自然科学基金(62071054);国家自然科学基金联合基金重点项目(U20A20167)。
摘 要:高血压是脑血管意外、心血管疾病和肾功能损害相关的主要危险因素之一。其症状和警告信号通常是模糊的,往往导致疾病被忽视,被称为“沉默的杀手”。中医脉诊操作明确、方法简单,通过脉搏信号来预测血压,使普通大众对自己的身体情况清楚明朗,早发现早治疗,同时可以促进中医脉诊客观化和科学化发展。本文基于现代化人工智能科学领域的发展,通过多种机器学习模型利用脉搏信号预测血压,以提升中医诊断的准确性,从而促进中医脉诊的现代化发展。实验表明,经过对比不同机器学习模型的结果,模型平均绝对误差可达到0.087,验证了基于机器学习的方法可以促进中医脉诊的客观化,且中医脉诊可以准确的预测人体血压。Hypertension is one of the major risk factors associated with cerebrovascular accidents,cardiovascular disease and renal impairment.Its symptoms and warning signs are usually vague,which often leads to the disease being overlooked and is known as the"silent killer".Chinese pulse diagnosis is a clear and simple method to predict blood pressure by pulse signals,which allows the general public to have a clear understanding of their health condition and early detection and treatment,and at the same time promotes the objectification and scientific development of Chinese pulse diagnosis.In this paper,based on the development in the field of modern artificial intelligence science,blood pressure is predicted by using pulse signals through various machine learning models in order to improve the accuracy of TCM diagnosis,thus promoting the modernization of TCM pulse diagnosis.The experiments show that after comparing the results of different machine learning models,the average absolute error of the models can reach 0.087,which verifies that the machine learning-based approach can promote the objectivity of TCM pulse diagnosis and that TCM pulse diagnosis can accurately predict human blood pressure.
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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