Artificial Intelligence

Artificial intelligence (AI) is becoming a crucial component of healthcare to help augment physicians and make them more efficient. In medical imaging, it is helping radiologists more efficiently manage PACS worklists, enable structured reporting, auto detect injuries and diseases, and to pull in relevant prior exams and patient data. In cardiology, AI is helping automate tasks and measurements on imaging and in reporting systems, guides novice echo users to improve imaging and accuracy, and can risk stratify patients. AI includes deep learning algorithms, machine learning, computer-aided detection (CAD) systems, and convolutional neural networks. 

GE and NVIDIA Join Forces to Accelerate Artificial Intelligence Adoption in Healthcare

GE Healthcare and NVIDIA today announced they will deepen their 10-year partnership to bring the most sophisticated artificial intelligence (AI) to GE Healthcare’s 500,000 imaging devices globally and accelerate the speed at which healthcare data can be processed.

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Just the beginning: 6 applications for machine learning in radiology beyond image interpretation

Discussions about machine learning’s impact on radiology might begin with image interpretation, but that’s only the tip of the iceberg. When it comes to realizing the technology’s full potential, it’s like Bachman Turner Overdrive sang many years ago: You ain’t seen nothing yet.

ICAD RECEIVES FDA APPROVAL FOR POWERLOOK TOMO DETECTION

First to market with innovative digital breast 3D tomosynthesis cancer detection and workflow solution, built on deep learning technology that improves efficiency and reduces reading time for radiologists

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First Patient Treated With LC Bead LUMI™ Radiopaque Embolic Bead Supported by Philips Live Image Guidance

Collaboration brings new tools to interventional radiologists and oncologists to help treat liver cancer and enhanced patient care.

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