Abstract: Aspects of the present application relate to techniques of diagnosing whether a pathogen (e.g., SARS-CoV-2) is present in a subject using infrared (IR) spectroscopy and machine learning techniques. The techniques use spectral data obtained from performing IR spectroscopy on a biological sample (e.g., saliva or nasal sample, or genetic material extracted therefrom) to generate a set of feature values. The feature values are provided as input to a machine learning model to obtain output indicating whether the pathogen is present in the biological sample. The output of the machine learning model may be used to determine a diagnosis result for a subject.

Abstract: Aspects of the present application relate to techniques of diagnosing whether a pathogen (e.g., SARS-CoV-2) is present in a subject using infrared (IR) spectroscopy and machine learning techniques. The techniques use spectral data obtained from performing IR spectroscopy on a biological sample (e.g., saliva or nasal sample, or genetic material extracted therefrom) to generate a set of feature values. The feature values are provided as input to a machine learning model to obtain output indicating whether the pathogen is present in the biological sample. The output of the machine learning model may be used to determine a diagnosis result for a subject.