METHODS: A set of primers and probe targeting rrs genes of 22 Leptospira spp. were designed and evaluated on 31 Leptospira isolates, 41 other organisms and 65 clinical samples from suspected patients.
RESULTS: The developed assay was able to detect as low as 20 fg Leptospira DNA per reaction (equivalent to approximately 4 copies) and showed high specificity against the tested leptospiral strains. No cross amplification was observed with the other organisms. During the evaluation of the confirmed clinical specimens, the developed assay was able to correctly identify all positive samples (n = 10/10). One amplification was observed in a negative sample (n = 1/55). The sequencing of the PCR product of the discordant sample revealed that the sequences were similar to those of L. interrogans and L. kirschneri.
CONCLUSION: The findings suggest that the developed Taqman qPCR assay is sensitive, specific and has potential to be applied in a larger subsequent study.
METHOD: To overcome the limitation, the use of artificial intelligence along with technical tools has been extensively investigated for AD diagnosis. For developing a promising artificial intelligence strategy that can diagnose AD early, it is critical to supervise neuropsychological outcomes and imaging-based readouts with a proper clinical review.
CONCLUSION: Profound knowledge, a large data pool, and detailed investigations are required for the successful implementation of this tool. This review will enlighten various aspects of early diagnosis of AD using artificial intelligence.