The result of study on technology usage of artificial intelligence for diagnostic trichomoniasis

Abstract

Introduction: Trichomoniasis has become one of the most common sexually transmitted diseases, representing 38.3 percent of total infections in Mongolia. We aimed to study the usage of diagnostic technology based on artificial intelligence for trichomoniasis. Materials and Methods: The study was conducted by using cross sectional design. As part of our study, we investigated the detection of artificial intelligence-based STIs using technology and other STIs diagnostic methods. Rather, the satisfaction survey of clinicians and medical professionals regarding the use of the above program was conducted by the General Laboratory Service of NCCD, AIDS and STIs. The artificial intelligence technology introduced into the diagnosis of STIs compared to other STIs diagnostic methods, including total of 90 smears were performed using wet mount, gram staining, and selective culture. The survey involved randomized sampling of 78 people, including laboratory physicians and assistants from district and provincial integrated hospitals and School of Biomedicine undergraduate students of MNUMS’s. Conclusion: When we compared TRI-VU and practically widely used method, gram staining, TRI-VU was 3.1 times fast than gram staining for detecting T. vaginalis. If the medical staff and physicians of the province and district’s STI bacteriological laboratory are overworked and there’s no time for making multiple works at the same time to accomplish during working hours, but also have welcomed TRI-VU3 program as a new technology for facilitating daily activities. The overall medical staff who participated in the study was significantly pleased with the new program’s functionality, believing that the introduction of TRI-VU3 program would improve the quality of diagnosis in STI’s bacteriological diagnosis.