Data Labeling & Human-in-the-Loop:

Accelerate Medical AI Development by Outsourcing Annotation

Healthcare organizations are increasingly using artificial intelligence (AI) to foster medical breakthroughs, improve care, make more accurate medical decisions, and lower costs. Developing and maintaining computer vision machine learning models is a big job that often requires millions of annotated images and videos.

Doctors and medical professionals are short on time and often short-staffed, so many innovators turn to outsourced workforces to accelerate the AI lifecycle. If you’re considering outsourcing, this eBook will provide valuable insight about choosing the right workforce to ensure that your healthcare data is annotated securely, scalably, cost-effectively, and accurately.

In this eBook, we explore:

• Opportunities and challenges in using AI to support diagnostics, research and development, robotics, and other medical use cases.
• An overview of data labeling, and how human-in-the-loop workforces can help reduce the burden on busy doctors and other medical professionals.
• Tips for choosing the right data annotation partner and ensuring that your medical imagery and video is securely handled, accurately annotated, and scaled to the level your models require.
• Top questions we hear from healthcare innovators about outsourcing complex and very large medical datasets.