Title: Smart algorithms for Colposcopic Automated Risk Assessment (CARE)
Abstract: Despite development of technologies that have rendered cervical cancer largely preventable in high- income countries, women living in low and middle-income countries (LMICs) continue to bear the brunt of cervical cancer incidence and mortality. One strategy–highly sensitive human papillomavirus (HPV) testing–has been shown to reduce the incidence and mortality from cervical cancer when coupled directly with outpatient treatment for women with HPV-positive results. The effectiveness of an HPV screen & treat strategy comes at the cost of overtreatment. To address this challenge, our group has developed a low-cost, mobile colposcope, called the Pocket Colposcope, which has shown high concordance with standard colposcopy. Further, we have developed a Colposcopy Automated Risk Evaluation (Pocket CARE) algorithm using convolutional neural networks to diagnose cervical pre-cancer among women who are screen positive, facilitating triage of patients without complex equipment or experts.
Publication Year: 2022
Publication Date: 2022-03-07
Language: en
Type: article
Indexed In: ['crossref']
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