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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AI differentiates between spondylitis MRIs as well as skilled radiologists

Research published online Sept. 3 in Scientific Reports concluded that an artificial intelligence (AI) algorithm can differentiate between tuberculous (TB) spondylitis and pyogenic spondylitis on MRI exams with the same level of expertise as skilled musculoskeletal radiologists.

Advanced imaging reveals concussed athletes may be returning too soon

Brain MRI scans of concussed university hockey players showed the protective tissue insulating brain cell fibers became jarred loose two weeks after injury—despite being cleared to return, research published in the Frontiers in Neurology revealed.

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‘Hive mind’ AI connects groups of radiologists, outperforms specialists or AI alone

A small group of experienced radiologists, connected by machine learning algorithms that enable them to work together as a “hive mind,” can achieve higher diagnostic accuracy than individual radiologists or machine learning algorithms alone, according to new research presented on Sept. 10 at the Society for Medical Imaging Informatics in Medicine (SIIM)’s Machine Intelligence in Medical Imaging conference.

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Radiologists connect via AI ‘hives’ to enhance pneumonia diagnosis

A new technique that connects a small group of radiologists together using artificial intelligence (AI) algorithms performed better than individual doctors or algorithms alone in detecting pneumonia on x-rays.

AI system predicts risk of developing type 2 diabetes

Shanghai researchers have created an artificial intelligence (AI) system designed to identify people most at risk for developing type 2 diabetes, according to a report by the South China Morning Post.

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AI can differentiate between tuberculous, pyogenic spondylitis as well as radiologists

A deep convolutional neural network (DCNN) can be trained to analyze MRI scans and differentiate between tuberculous spondylitis and pyogenic spondylitis, according to a new study published in Scientific Reports.

Mapping CT scan locations on computational humans may improve patient dose monitoring

A new algorithm that can automatically map CT scan locations of patients on computational human phantoms may trump manual mapping techniques for patient dose monitoring, clinical trials and epidemiologic studies, detailed a study published online Sept. 5 in the Journal of Digital Imaging.

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Exact Imaging, Cambridge Consultants announce plan to improve prostate cancer detection using AI

Toronto-based Exact Imaging and Cambridge, U.K.-based Cambridge Consultants have announced a new international partnership focused on improving the way specialists visualize and detect prostate cancer.

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