ImageBiopsy Lab uses model-assisted labeling to increase efficiency by 160%
Since 2016, ImageBiopsy Lab has been building AI applications to help physicians and the medical community at large better understand and diagnose musculoskeletal diseases (MSK), which affect 1.7 billion people worldwide. Today, the team focuses on optimizing the radiological workflow via automation and standardization to enable the early detection and prevention of MSK. This automated decision support allows orthopedists and radiologists to assess and predict bone health by turning images into actionable information.
“We use it to connect the dots, discover new correlations between the image and the patient outcome. This will fundamentally change the way healthcare will be done in the future,” says ImageBiopsy Lab Co-founder and COO Christoph Götz. The team has optimized their ML development process by using AI to pre-sort massive datasets and employing a model-assisted labeling workflow to pre-annotate filtered datasets. As a result, the team has increased their labeling efficiency by 160%.
Learn more about how ImageBiopsy Lab built their data engine at Accelerate 2021, on October 21-22. Register today!