Diagnostic accuracy of artificial intelligence-based multi-spectrum analysis for molecular fingerprint detection of SARS-CoV-2.

ABSTRACT: Reverse transcription-polymerase chain reaction (RT-PCR) is the reference standard for COVID-19 diagnosis, but the need for rapid, reproducible, and cost-effective diagnostic tools remains. This study investigated the diagnostic performance of a novel artificial intelligence-based multispectrum analysis (MSA, AP23) technique that detects the biomolecular fingerprint of severe acute respiratory syndrome coronavirus 2. A prospective, double-blinded observational design was used, involving 3614 volunteers. The artificial intelligence was trained with 2448 samples, validated with 816, and tested against RT-PCR using a blinded set of 350 samples. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated. During validation, MSA achieved 88.4% sensitivity,

SUBMITTER: Tayfur I 

PROVIDER: S-EPMC12114054 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature