VisualCheck
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Double-check with VisualCheck VisualCheck provides clinicians with an automated clinical decision support tool based on machine learning and augmented intelligence (AI) to assess for 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. While not a replacement for the clinical judgment of the provider, VisualCheck is an additional support tool to ensure an enhanced clinical assessment. VisualCheck is intended for practitioners who are trained in cervical examinations. “We set out to create smart medical solutions by combining the computational power of smart mobile devices with advanced imaging algorithms and Artificial Intelligence. The outcome promises to be a revolution in cervical cancer screening.” David Levitz, PhD Co-Founder & Chief Scientist at MobileOD

Sensitivity: 81% Specificity: 84% Based on results of initial clinical validation “…this is the first utilization of real-time AI for patient management at the point of care... These results suggest that AI can provide an immediate answer that is mostly consistent with colposcopic impressions…” Step-by-step VisualCheck Utilization of machine learning classifiers in a cervical cancer screening camp in rural China, Andrew Goldstein, Sarah Bedell, Cathy Sebag, Lior Lobel, David Levitz, Poster accepted to IPVC 2020 Perform cervical cancer evaluation according to standard guidelines using the...