Google的AI 模型HAAR与Salcit Technology合作, 使用音频样本以94%的精确度检测早期肺结核症状。 Google's AI model HeAR, in partnership with Salcit Technologies, detects early tuberculosis signs with 94% accuracy using audio samples.

Google的AI模型“健康声学表征”(HeAR)通过3亿个音频样本培训,识别呼吸道疾病的声音,如咳嗽、鼻吸和呼吸困难。 Google's AI model, Health Acoustic Representations (HeAR), identifies respiratory illness sounds, such as coughs, sniffles, and labored breathing, through 300 million audio sample training. HeAR的数据与印度卫生技术公司Salcit Technology合作,用于Salcit的Swaasa应用程序,以94%的精确度检测结核病的早期症状。 Partnering with Indian health tech company Salcit Technologies, HeAR's data is used in Salcit's app, Swaasa, to detect early signs of tuberculosis with 94% accuracy. 这种低成本、非侵入性技术可以在资源有限的地区使获得医疗保健的机会发生革命性变化。 This low-cost, non-invasive technology could revolutionize healthcare access in regions with limited resources.