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. 

layoffs staff cuts termination workforce

Verily lays off 15% of workers months after raising $1B

Verily, the life sciences subsidiary of Google parent company Alphabet, is laying off 15% of its workforce just months after raising $1 billion in a funding round.

Jakob Weiss, MD, a radiologist affiliated with the Cardiovascular Imaging Research Center at Massachusetts General Hospital and the AI in Medicine program at the Brigham and Women’s Hospital in Boston, helped develop an deep learning AI algorithm that can assess a patient's biological age and risk assess patients for various diseases. #RSNA #AI #ImagingAI

VIDEO: AI predicts heart disease risk using single chest X-ray

Jakob Weiss, MD, was the lead author on a study that used AI to determine a patient's cardiovascular risks based on a standard chest X-ray.

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AI in radiology: How do rad techs feel about its use?

Many radiologic technologists strongly feel that AI technologies should be incorporated into the curriculum for today’s emerging radiographers. 

Google Health develops AI models for more accurate gestational age estimation

The models do not require manual measurements from a sonographer to estimate GA. Instead, they are able to make use of ultrasound images and videos.

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Biological ‘brain age’ could help pave the way for more personalized medicine

AI-powered analysis can now assess cognitive decline by noting gaps in chronological versus biological “brain age.”

Emerging imaging technologies boosted by COVID research

As the field of radiology research adapted to withstand the pandemic’s challenges, it morphed in some decidedly beneficial ways.

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AI 'candidate' fails to pass mock radiology boards

Out of 10 mock exams, the AI candidate passed two, achieving an overall accuracy of 79.5%, suggesting that the candidate is not quite “ready to graduate.” 

York University researchers demonstrate how AI can help predict brain metastasis outcomes

AI bests humans at predicting outcomes for brain radiotherapy patients

The new technology could help develop more tailored treatment plans.