Are you considering outsourcing data labeling work while developing medical AI or computer vision solutions? Read these data security tips.
Doctor shortages are impacting healthcare innovators’ ability to label data for computer vision solutions. Outsourcing the work will help.
Computer vision improves patient care, streamlines medical decisions, and lowers costs. Ask these questions before outsourcing healthcare data annotation.
Recap of our chat with V7 about medical AI data annotation while creating a dataset of COVID-19 X-rays for clinical use and diagnostic AI development.
Healthcare providers face mounting pressure to increase clinical efficiency and improve patient outcomes. The need for automation and AI is now.
The rise of medical AI solutions shows great promise, but there are still important hurdles to overcome, such as concerns about privacy and data accuracy.
From data collection to training and deploying working models, the development of medical AI comes with many important challenges and opportunities.
From faster drug discovery to robotic surgery, AI is transforming the healthcare sector with promises of improved patient care and reduced costs.
AI is transforming healthcare by arming practitioners with more information at the right times to make better decisions and fewer errors. Here’s how image annotation makes it ...
Image annotation holds great promise for these centuries-old industries that rely heavily on visual data and are ripe for AI innovation.
CloudFactory and V7 Labs annotated chest x-rays and trained ML models to identify issues including COVID-19. The dataset is now available for research.
Healthcare companies transcribing high volume of medical record need to strike a balance between speed and accuracy.