OptoAgent：一种用于教室环境中机会性视力微筛查的可信多智能体框架
OptoAgent: A Trustworthy Multi-Agent Framework for Opportunistic Vision Micro-Screening in Classroom Environments
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中文总结 AI 辅助
针对儿童视力问题发现滞后，提出SightSentinel架构，利用教室墙面显示器和八个智能体进行机会性视力微筛查，通过质量门控和纵向累积证据生成视力关注评分，并验证其转诊决策的有效性。
中文摘要 AI 辅助
视力下降的儿童往往并不知道自己存在问题。儿童会适应这种状况，靠近观看，并且很少报告困难，因此这个问题可能在成年人的注意之前，伴随多年的学校教育而存在。学校筛查部分解决了这一问题，但它按计划进行，依赖人员配备，并且与困难出现的课堂时刻相分离。基于智能手机和网络的视力测试扩大了可及性，但每一种测试仍然需要有人启动测试。我们提出了SightSentinel，一种将儿童已经阅读的墙面显示器转变为重复筛查点的架构。普通的教育内容携带短小的校准视标探针，八个专门的智能体分工协作。感知智能体从每次遭遇中恢复观看距离、识别准确度、接近行为、注视稳定性、反应延迟和双眼差异。一个质量智能体丢弃在不良几何条件、光线不佳或注意力不集中的情况下采集的观察数据。一个纵向智能体仅累积针对儿童自身基线的幸存证据，而一个编排器报告通过安全门路由的视力关注评分，其输出范围排除诊断、屈光、处方和安抚。设计问题在于，许多廉价、嘈杂且经过良好门控的遭遇是否能达到一次计划测试迟到或遗漏的转诊决定。我们阐述了公式化表述、架构、针对临床参考标准的四阶段验证协议，以及应拒绝该方法的条件。
英文摘要
A child with reduced distance vision often does not know that anything is wrong. Children adapt, move closer, and rarely report the difficulty, so the problem can survive years of schooling before an adult notices. School screening addresses part of this, but it runs on a schedule, depends on staffing, and is separated from the classroom moments where the difficulty appears. Smartphone and web-based acuity tests have widened access, yet every one of them still needs somebody to start a test. We present SightSentinel, an architecture that turns a wall display a child already reads from into a recurring screening site. Ordinary educational content carries short calibrated optotype probes, and eight specialized agents divide the work. Perception agents recover viewing distance, recognition accuracy, approach behavior, gaze stability, response latency, and interocular difference from each encounter. A quality agent discards observations taken under bad geometry, poor lighting, or inattention. A longitudinal agent accumulates only the surviving evidence against the child's own baseline, and an orchestrator reports a Vision Concern Score routed through a safety gate whose output range excludes diagnosis, refraction, prescription, and reassurance. The design question is whether many cheap, noisy, well-gated encounters can reach a referral decision that one scheduled test reaches late or misses. We state the formulation, the architecture, a four-stage validation protocol against clinical reference standards, and the conditions under which the approach should be rejected.
发表机构
- Islamic University of Madinah（麦地那伊斯兰大学）
- King Fahd University of Petroleum and Minerals（法赫德国王石油矿产大学）
- The Islamia University of Bahawalpur（巴哈瓦尔布尔伊斯兰大学）
机构由 AI 辅助整理，请以论文原文为准。
