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https://www.selleckchem.com/products/AZD2281(Olaparib).html 5%), however, only 50.4% (n = 53) of those providers planned to use VH regularly once able to see patients safely in clinic again. Conclusions While the majority of U.S. eye care providers who responded were not using VH before the COVID-19 pandemic, just months into the U.S. outbreak, 77.4% were using VH in their daily practice. In general, providers used these platforms for urgent examinations, adnexal disease, and postoperative care most often. The majority felt the transition was a positive one, however, only half planned to continue regular use of VH once the pandemic ended.Background This study aimed to compare artificial intelligence (AI)-aided colonoscopy with conventional colonoscopy for polyp detection. Methods A systematic literature search was performed in PubMed and Ovid for randomized clinical trials (RCTs) comparing AI-aided colonoscopy with conventional colonoscopy for polyp detection. The last search was performed on July 22, 2020. The primary outcome was polyp detection rate (PDR) and adenoma detection rate (ADR). Results Seven RCTs published between 2019 and 2020 with a total of 5427 individuals were included. When compared with conventional colonoscopy, AI-aided colonoscopy significantly improved PDR (P  less then  .001, odds ratio [OR] = 1.95, 95% confidence interval [CI] 1.75 to 2.19, I2 = 0%) and ADR (P  less then  .001, OR = 1.72, 95% CI 1.52 to 1.95, I2 = 33%). Besides, polyps in the AI-aided group were significantly smaller in size than those in conventional group (P = .004, weighted mean difference = -0.48, 95% CI -0.81 to -0.15, I2 = 0%). In addition, AI-aided group detected significantly less proportion of advanced adenoma (P = .03, OR = 0.70, 95% CI 0.50 to 0.97, I2 = 46%), pedicle polyps (P  less then  .001, OR = 0.64, 95% CI 0.49 to 0.83, I2 = 0%), and pedicle adenomas (P  less then  .001, OR = 0.60, 95% CI 0.44 to 0.80, I2 = 0%). Conclusion AI-aided colonoscopy could signifi

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