Abstract：
Tuberculosis (TB) is a contagious disease that causes 1.5 million deaths per year globally. Early diagnosis of TB patients is critical to control its spread. However, standard TB diagnostic tests such as sputum culture take days to weeks to produce results. Here, we demonstrate a quick, portable, easy-to-use, and non-invasive optical sensor based on sputum samples for TB detection. The probe uses Raman spectroscopy to detect TB in a patient\'s sputum supernatant. We deploy a machine-learning algorithm, principal component analysis (PCA), on the acquired Raman data to enhance the detection sensitivity and specificity. On testing 112 potential TB patients, our results show that the developed probe\'s accuracy is 100% for true-positive and 93.4% for true-negative. Moreover, the probe correctly identifies patients on TB medication. We anticipate that our work will lead to a viable and rapid TB diagnostic platform.
摘要：
结核病（TB）是一种传染性疾病，每年在全球造成150万人死亡。结核病患者的早期诊断对于控制其传播至关重要。然而,标准的结核病诊断测试，如痰培养，需要几天到几周才能产生结果。这里,我们展示了一个快速的，便携式，易于使用，基于痰液样本的非侵入式光学传感器用于TB检测。该探针使用拉曼光谱检测患者痰上清液中的TB。我们部署了机器学习算法，主成分分析(PCA)，对采集的拉曼数据，以提高检测灵敏度和特异性。在测试112名潜在结核病患者时，我们的结果表明，开发的探针的准确性是100％的真阳性和93.4％的真阴性。此外，该探针正确识别了使用结核病药物的患者。我们预计我们的工作将导致一个可行和快速的结核病诊断平台。
