Vaginal infections, especially bacterial vaginosis (BV), are a major concern for women’s health. Current diagnosis methods are subjective and often miss the mark, particularly for asymptomatic women. Researchers have developed a promising new approach using a test that analyzes the fern-like patterns formed when cervical mucus dries on a slide. Healthy mucus forms distinct fern patterns, while unhealthy mucus (associated with BV) has a disrupted structure.
We’re developing an image-based algorithm to analyze these patterns and generate a “FernScore,” which suggests the likelihood of BV. This technology has the potential to revolutionize BV diagnosis, leading to better treatment options and improved women’s health.