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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American College of Radiology, RSNA ask feds to pump the brakes on autonomous AI

Top officials from the two groups believe it’s unlikely the FDA can provide assurances of such technology’s safety in imaging care, absent further testing, surveillance and other methods of oversight.

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Dutch artificial intelligence firm collects $2.3M to fuel prostate cancer solution

The money comes by way of the European Innovation Council Accelerator and balloons Quantib's fundraising total to almost $13.5 million (USD). 

4 takeaways from a Harvard hospital’s homegrown COVID forecasting

Researchers at Boston’s Beth Israel Deaconess Medical Center are sharing insights they gained while building a locally focused, AI-aided model for anticipating COVID-19’s next moves.  

Brain iron buildup is associated with cognitive decline in Alzheimer’s patients

The MRI findings may push treatment research toward drugs that eliminate excess iron from the body, commonly known as chelators.

Will EHR-enabled AI size up doctors for data-demanding patients?

The COVID-19 crisis has worsened or exposed myriad problems in healthcare delivery. One is the way patients find physicians and hospitals. AI can help with that.

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Hospital alerts radiologists of new post-COVID-19 disease appearing in children

Evelina London Children's Hospital recently experienced an "unprecedented cluster" of a new condition known as Multisystem Inflammatory Syndrome in Children, and is warning it's imaging colleagues in the U.S. to be on the lookout.

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Machine learning provides radiologists a cost-effective assist to deduce lung cancer severity from CT

Stanford University experts call their new neural network “LungNet” and say the system has delivered consistent, fast and accurate interpretation of computed tomography scans.

Nuance AI Marketplace Accelerates AI Adoption for Radiologists to Improve Patient Outcomes and Reduce Burnout

Leveraging the widespread deployment of Nuance's PowerScribe reporting solution and PowerShare Network, the AI Marketplace facilitates the seamless utilization of AI for diagnostic imaging by providing the nation's largest two-sided network for imaging AI.