How machine learning could help doctors improve the reading of medical images

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The radiology world has been abuzz with discussions of machine learning and what artificial intelligence may mean for the future of the field. The goal is for the technology to quickly scan medical images and prioritize abnormal results, allowing doctors to spend their time on the more difficult cases. The machines would also provide a check on human error. Companies are jumping on board. IBM Watson Health, which acquired enterprise imaging software company Merge Healthcare in 2015, plans to put its Watson supercomputer to work analyzing medical images.


How machine learning could help doctors improve the reading of medical images

#artificialintelligence

CHICAGO - The radiology world has been abuzz with discussions of machine learning and what artificial intelligence may mean for the future of the field. The goal is for the technology to quickly scan medical images and prioritize abnormal results, allowing doctors to spend their time on the more difficult cases. The machines would also provide a check on human error. Companies are jumping on board. IBM Watson Health, which acquired enterprise imaging software company Merge Healthcare in 2015, plans to put its Watson supercomputer to work analyzing medical images.


How machine learning could help doctors improve the reading of medical images

#artificialintelligence

The radiology world has been abuzz with discussions of machine learning and what artificial intelligence may mean for the future of the field. The goal is for the technology to quickly scan medical images and prioritize abnormal results, allowing doctors to spend their time on the more difficult cases. The machines would also provide a check on human error. Companies are jumping on board. IBM Watson Health, which acquired enterprise imaging software company Merge Healthcare in 2015, plans to put its Watson supercomputer to work analyzing medical images.


How machine learning could help doctors improve the reading of medical images

#artificialintelligence

The goal is for the technology to quickly scan medical images and prioritize abnormal results, allowing doctors to spend their time on the more difficult cases. The machines would also provide a check on human error. Companies are jumping on board. IBM Watson Health, which acquired enterprise imaging software company Merge Healthcare in 2015, plans to put its Watson supercomputer to work analyzing medical images. One of its projects, presented at the Radiological Society of North America's annual conference, focuses on research around aortic stenosis, a heart condition that occurs when the aortic valve narrows.


IBM Watson aligns with 16 health systems and imaging firms to apply cognitive computing to battle cancer, diabetes, heart disease

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IBM Watson Health has formed a medical imaging collaborative with more than 15 leading healthcare organizations. The goal: To take on some of the most deadly diseases. The collaborative, which includes health systems, academic medical centers, ambulatory radiology providers and imaging technology companies, aims to help doctors address breast, lung, and other cancers; diabetes; eye health; brain disease; and heart disease and related conditions, such as stroke. Watson will mine insights from what IBM calls previously invisible unstructured imaging data and combine it with a broad variety of data from other sources, such as data from electronic health records, radiology and pathology reports, lab results, doctors' progress notes, medical journals, clinical care guidelines and published outcomes studies. As the work of the collaborative evolves, Watson's rationale and insights will evolve, informed by the latest combined thinking of the participating organizations.