MEDICAL AI COMPANY (MAI) Making time for innovation with scalable image annotation
公司规模
11-200
地区
- America
国家
- United States
产品
- CloudFactory Managed Workforce
- MAI Custom Annotation Tool
技术栈
- Machine Learning
- Computer Vision
- Semantic Segmentation
- 3D Point Cloud
- Sensor Fusion Systems
实施规模
- Enterprise-wide Deployment
影响指标
- Customer Satisfaction
- Digital Expertise
- Productivity Improvements
技术
- 分析与建模 - 计算机视觉软件
- 分析与建模 - 机器学习
- 功能应用 - 远程监控系统
适用行业
- 医疗保健和医院
适用功能
- 产品研发
- 质量保证
用例
- 计算机视觉
- 预测性维护
- 远程资产管理
服务
- 数据科学服务
- 系统集成
关于客户
MAI provides an image database for research and evidence-based healthcare and needed a way to label thousands of images quickly and accurately to further its product offering. Managing in-house staff, even on a contract basis, was time-consuming and expensive. But the image files are big and the task is complex, so outsourcing the task seemed daunting as well. Within months of choosing CloudFactory’s managed workforce option, MAI completed 12 additional imagery databases to improve its product and is sold on our managed workforce process.
挑战
MAI needed the labeling work done by a consistent group of individuals who could log on remotely to the company’s own annotation tool which is custom-designed with machine learning components built-in. The work is critical to MAI’s efforts to stay ahead of the curve in providing AI-based image databases that enhance medical professionals’ understanding of health issues. One of its goals is to provide predictive advice based on tagging and analyzing images throughout a patient’s lifespan in order to enhance preventative care. MAI’s owner researched multiple companies looking for the best image tagging help. He was worried about crowdsourcing because he didn’t think the quality would be there. Some companies had preconceived ways of working with clients and were not interested in having staff work directly on his platform. Additionally, he needed workers used to dealing with images because each batch is unique in terms of what is being tagged.
解决方案
MAI chose CloudFactory for its flexibility and its experience working with other computer vision companies. CloudFactory workers are trained in a wide array of use cases from bounding boxes and semantic segmentation to 3D point cloud and sensor fusion systems. In addition, CloudFactory has a set of best practices developed from annotating millions of images and videos over the last ten years. Initially, MAI was concerned that data labelers without a medical background might not be successful, but he was pleasantly surprised. He provided some documents and recorded videos for training. CloudFactory has done a great job, and if something isn’t quite right, feedback is given and improvements are made. CloudFactory has also provided valuable feedback on MAI's tool.
运营影响
数量效益
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