Abstract
Abstract
Traditional disease screening methods often rely on protein biomarkers or imaging, which are somewhat constrained by their sensitivity, invasiveness, and limitation in detecting diseases at earlier stages. To achieve both noninvasive and early warning of diseases or physiology change, monitoring gaseous biomarkers such as volatile organic compounds (VOCs) and nitric oxide (NO) in exhaled breath is a promising solution. It has been demonstrated that these biomarkers as a group change rapidly in response to alterations in human physiology, which allows rapid noninvasive earlier screenings of asthma, lung cancer, coronavirus disease 2019 (COVID-19) and other diseases. Interestingly, this has also been demonstrated for real-time monitoring of air toxicity by resolving rats’ breath-borne biomarkers. Here, we propose the use of artificial intelligence (AI) and breath-borne gaseous biomarkers to construct the “fingerprint pattern” of a specific disease or certain environmental hazards for early warning.