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Using both a quality classifier and a predictive algorithm, VisualCheck predicts how highly trained colposcopists may determine findings of the cervix.
About
VisualCheck provides clinicians with an automated clinical decision support tool based on machine learning and augmented intelligence (AI) to assess normal and abnormal cervical findings. Using both a quality classifier and a predictive algorithm, VisualCheck predicts how highly trained colposcopists may determine findings of the cervix. VisualCheck runs on the Enhanced Visual Assessment (EVA) System, an FDA cleared and CE marked smart mobile colposcope. The colposcope combines high-quality optics, image, and video capture with secure, HIPAA and GDPR-compliant online data management. Additionally, the EVA System has tele-gynecology features that enable remote practitioners to speak to one another in real-time.
Key Benefits
Cervical cancer remains a leading cause of mortality and morbidity for women worldwide, despite great advancements made in diagnostic tests, vaccines, and treatment. Women still face many barriers to accessing such advancements. Long waits or burdensome travel to receive diagnostic results from laboratory-based tests such as the Pap or HPV test delay treatment and lead to loss to follow up and resulting in nearly 350,000 unnecessary deaths every year. Current approaches to cervical cancer screening - Pap cytology and HPV detection - require laboratories that need infrastructure to collect and process samples. Other colposcopes are bulky, hard to transport, and have limited connectivity. In contrast, the EVA System is markedly more affordable, fully portable, and is infinitely smarter with several online features and AI tools to support immediate point-of-care clinical decision making and service packages to free the screener from the requirements of laboratories or nearby expertise.
Applications
The EVA System has the potential to impact every woman on the planet. Over 70,000 women have already been screened with the EVA System across 29 countries around the world, primarily in low-resource settings and rural areas. An estimated 4,000 cases of pre-cancer have been identified, saving thousands of lives and preventing unnecessary suffering to those women’s families and communities. Initially, MobileODT will use the EVA System to deploy the VisualCheck algorithm with our strategic partners in South Korea, Europe, India and Sub-Saharan Southern Africa. We in turn are developing a technology (Universal VisualCheck) that will convert digital images from standard digital colposcopes to an EVA image so we may run these colposcope images on our AI algorithm as well. This will enable healthcare providers (OB-GYN, Family Physicians, Nurse Practitioners) who are not specialists in cervical cancer or well versed in visual assessment of cervical cancer, to become point-of-care providers for screening. This is a huge shift in current care methods that are less accurate and carry a higher risk for women to not return to treatment or loss to follow up while waiting for results.