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. 

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New AI algorithm predicts how well deaf children will learn language

Researchers have created a new algorithm that uses brain scans to predict language ability in deaf children after they receive a cochlear implant, according to a study published in the Proceedings of the National Academy of Sciences.

AI in Healthcare Summit to explore applications in robotics, imaging, interoperability

The two-day AI in Healthcare Summit on Thursday and Friday, Jan. 18 and 19, at the Harvard Club in Boston offers an in-depth discussion on the current state of the healthcare AI industry, AI-driven advancements in medical imaging and diagnostics, surgical robotics, patient engagement, integration and interoperability opportunities and challenges, bringing the human aspect back to healthcare, legal considerations and AI’s role in value-based care.

vRad announces new patent for escalating radiology procedures through AI

vRad, a MEDNAX company, announced this week that it has secured a patent for using artificial intelligence (AI) to escalate high-priority radiology procedures.

Researchers use machine learning to detect fractures in plain radiographs

Machine learning using deep convolutional neural networks (CNNs) can be used to detect fractures in plain radiographs, according to a new study published in Clinical Radiology.

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Software using machine learning algorithms accurately audits radiologist compliance

Imaging groups throughout the United States have moved to standardized radiology reports in recent years, and it’s a trend that continues to pick up steam. One side effect of this change is that leaders must then perform long, labor-intensive manual audits of their team’s reports to confirm compliance. But what if groups could somehow perform an automated audit, making those pesky manual audits a thing of the past?

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

Around the web

CMS has more than doubled the CCTA payment rate from $175 to $357.13. The move, expected to have a significant impact on the utilization of cardiac CT, received immediate praise from imaging specialists.

The all-in-one Omni Legend PET/CT scanner is now being manufactured in a new production facility in Waukesha, Wisconsin.

After reviewing years of data from its clinic, one institution discovered that issues with implant data integrity frequently put patients at risk. 

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