ARTIFICIAL INTELLIGENCE IN THE STUDY OF PHYSIOLOGICAL PARAMETERS OF THE HUMAN RESPIRATORY SYSTEM

Modern artificial intelligence technologies offer new opportunities for analyzing physiological parameters of the human respiratory system. Machine learning algorithms enable processing large data sets, identifying patterns, and predicting lung function based on standard respiratory parameters. This study analyzed data from 60 volunteers across three age groups using an AI system to assess vital capacity, respiratory rate, and minute volume. Results showed that the AI system can accurately classify age-related respiratory function characteristics and identify functional decline in elderly participants. The use of AI can improve diagnostic accuracy, reduce analysis time, and improve the risk prediction of respiratory disorders.现代人工智能技术为人类呼吸系统生理参数的分析提供了全新机遇。机器学习算法可处理大规模数据集、识别数据模式，并基于标准呼吸参数预测肺功能。本研究借助人工智能（AI）系统，对覆盖三个年龄组的60名志愿者的数据展开分析，以评估肺活量、呼吸频率与每分通气量三项指标。研究结果显示，该AI系统能够精准分类与年龄相关的呼吸功能特征，并识别老年受试者的呼吸功能衰退情况。人工智能的应用可提升诊断准确率、缩短分析耗时，并优化呼吸系统疾病的风险预测能力。