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Provectus > 实例探究 > 通过机器学习增强儿科照片筛查
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GoCheck Kids Leverages Machine Learning to Enhance Pediatric Photoscreening

技术
  • 分析与建模 - 计算机视觉软件
  • 分析与建模 - 机器学习
适用行业
  • 水泥
  • 教育
适用功能
  • 维护
  • 产品研发
用例
  • 临床图像分析
  • 施工管理
服务
  • 数据科学服务
  • 培训
挑战
GoCheck Kids 需要通过机器学习增强其儿科照片筛查应用程序的图像分类部分。他们需要强大且有弹性的机器学习基础设施,以便更快、更经济高效地在超过一百万张图像的数据集上运行实验。
关于客户
GoCheck Kids 是一款经过临床验证、易于使用、全面的照片筛选和视力应用程序,有助于预防 1-18 岁儿童的视力障碍、失明和与视力相关的学习挑战。目前,他们为美国和欧洲的 6,500 多个儿科团队提供服务。
解决方案
GoCheck 与 Amazon Web Services (AWS) 和 Provectus 合作,构建部署在 AWS 上的安全且可审计的 ML 训练基础设施。该基础设施包括实验跟踪、模型版本控制和用于持续数据重新标记和重新训练的主动学习管道。 Provectus 还将机器学习解决方案集成到移动应用程序和 GoCheck 的业务工作流程中。
运营影响
  • The new machine learning infrastructure on AWS supported regular model retraining, evaluation, tuning, and improvements to machine learning models as new labeled data and feedback arrived. More efficient data preparation and faster experimentation enabled GCK to increase the recall of machine learning models by 3X while preserving its precision. This brought in both short and long-term benefits, including improved usability of the app and increased customer satisfaction, by decreasing the final results of 'child not looking' by asking the user to retake the image. The robust and resilient infrastructure for machine learning bolsters GoCheck's quick, sustainable growth in the vision screening market. The GCK application is now equipped with advanced machine learning algorithms that further enable accurate and convenient photoscreening for a wide range of conditions, including amblyopia. Better access to affordable eye screening with GCK means that millions of children will be diagnosed in time, and will not suffer from vision impairments and blindness as adults.

数量效益
  • Increased the recall of machine learning models by 3X while preserving precision

  • Conducted over 100 large-scale experiments in three weeks by three machine learning engineers

  • 95% of machine learning engineers' time is now exclusively dedicated to experimentation

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