Google is launching a set of tools meant to make medical images more interoperable and help organizations develop artificial intelligence and machine learning models around them.
Billions of medical images are scanned each year, and imaging data makes up 90% of all healthcare data, according to research from Cornell University.
The images have been a focus for efforts looking to leverage technology to improve the quality of care delivery, with hopes that AI can mine insights and arrive at diagnoses faster and more accurately than human clinicians, while lowering the workload on radiologists.
Google’s new Medical Imaging Suite includes cloud-based file storage with secure data exchange capabilities, automated image labeling through AI-assisted annotation, and tools to create training datasets for algorithms and accelerate the development of scalable machine learning models with less code, according to the tech giant.
Some Google Cloud clients have already begun using the suite of digital tools, including Hackensack Meridian Health in New Jersey, which is using it to de-identify images in order to build AI algorithms capable of predicting metastasis in patients with prostate cancer.
In addition, medtech company Hologic is using the tools to expand capabilities for its digital cytology platform for labs, which helps cytologists and pathologists identify precancerous lesions and cervical cancer cells in patients, Google said in a release on the product.
Funding for AI in healthcare has exploded over the past few years due to its potential to reshape how healthcare is delivered in the U.S., though potential benefits have largely yet to materialize. The technology faces roadblocks for use, including clinician buy-in, regulatory uncertainty and concerns about health equity and bias.
Radiology is one area of promise for AI, as proponents of the technology argue AI systems can analyze data that’s not visible to the human eye, making it a valuable diagnostic tool.
A number of healthcare organizations are implementing AI to create, analyze and make sense of medical images, including New York University Langone Health, which has partnered with Facebook’s AI team to develop an algorithm that allows an MRI to take just 15 minutes instead of an hour, and also developed a tool to predict the probability of breast cancer in MRI scans that’s capable of reducing unnecessary biopsies by up to 20%.
