首页|University of Oxford Reports Findings in Artificial Intelligence [Artificial Intelligence (AI) Reveals Ethnic Disparities in Cataract Detection and Treatment]
University of Oxford Reports Findings in Artificial Intelligence [Artificial Intelligence (AI) Reveals Ethnic Disparities in Cataract Detection and Treatment]
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Artificial Intelligenc e is the subject of a report. According to newsreporting from Oxford, United Ki ngdom, by NewsRx journalists, research stated, “The aim of this workis to ident ify patients at risk of limited access to healthcare through artificial intellig ence using a nameethnicityclassifier (NEC) analyzing the clinical stage of cat aract at diagnosis and preoperative visual acuity.This retrospective, cross-sec tional study includes patients seen in the cataract clinic of a tertiary care hospital between September 2017 and February 2020 with subsequent cataract surgery in at least one eye.”The news correspondents obtained a quote from the research from the University o f Oxford, “Weanalyzed 4971 patients and 8542 eyes undergoing surgery. The NEC i dentified 360 patients with namesclassified as ‘non-German’ compared to 4611 cl assified as ‘German’. Advanced cataract (7 vs. 5%; p =0.025) was s ignificantly associated with group ‘non-German’. Mean best-corrected visual acui ty in group‘non-German’ was 0.464 ± 0.406 (LogMAR), and in group ‘German’ was 0 .420 ± 0.334 (p = 0.009).This difference remained significant after exclusion o f patients with non-lenticular ocular comorbidities.Surgical time and intraoper ative complications did not differ between the groups. Retrobulbar or general anesthesia was chosen significantly more frequently over topical anesthesia in gro up ‘non-German’ comparedto group ‘German’ (24 vs. 18% respectivel y; p<0.001). This study shows that artificial intelligence isable to uncover health disparities between people with German compared to no n-German names usingNECs. Patients with non-German names, possibly facing vario us social barriers to healthcare access suchas language barriers, have more adv anced cataracts and worse visual acuity upon presentation.”
OxfordUnited KingdomEuropeAnesthesiaArtificial IntelligenceEmerging TechnologiesMachine LearningPain MedicineRisk and Prevention
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