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. 

Conventional imaging did not detect the abnormalities, which MRI scans identified up to one year after infection.

AI determines difference between lung cancers with 97% accuracy

Using artificial intelligence, researchers at the NYU School of Medicine can correctly distinguish between two different types of lung tumors—adenocarcinoma and squamous cell carcinoma—with 97 percent accuracy.

September 18, 2018

‘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.

September 11, 2018

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.

September 10, 2018
A survey conducted by the Ann and Robert H. Lurie Children's Hospital of Chicago found more than 75% of parents are generally receptive to the use of artificial intelligence (AI) tools in the management of children with respiratory illnesses in the emergency department (ED). However, some demographic subgroups, including non-Hispanic black and younger age parents, had greater reservations about the use of these technologies. 

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.

September 7, 2018

AI-based breast cancer detection method inspired by a classic video game

The creators of a fully automated medical image analysis program to detect breast tumors was inspired by the classic video game Tetris. It is also almost twice as fast at finding lesions as existing techniques and just as accurate.

September 6, 2018

Deep learning system accurately assesses liver fibrosis using CT images

A deep learning system (DLS) designed to assess liver fibrosis using CT images was found to be highly accurate, according to a new study published in Radiology.

September 5, 2018

Fujifilm, Indiana University team up to study AI, develop new imaging technology

Fujifilm Corporation and the Indiana University School of Medicine in Indianapolis have announced a new research agreement that will focus on applying artificial intelligence (AI) to medical imaging diagnostic support systems.

August 28, 2018

AI algorithm detects lung nodules with 95% accuracy

Researchers at the University of Central Florida’s Center for Research in Computer Vision have created an artificial intelligence (AI) algorithm that can detect specks of lung cancer in CT scans with 95 percent accuracy.

August 23, 2018

Around the web

The newly approved AI models are designed to improve the detection of pulmonary embolisms and strokes in patients who undergo CT scans.

Using CT to perform coronary artery calcium scoring on symptomatic chest pain patients can deliver significant value, according to a new data published in Radiology

Peninsula Imaging told Mary Raver in 2014 that a cancerous growth was benign. She now has 18 months to live.

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