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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ESR and GE Healthcare announce AI partnership for ECR 2019

The European Society of Radiology (ESR) and GE Healthcare have announced a new partnership focused on artificial intelligence (AI) for the European Congress of Radiology (ECR) 2019 in Vienna, Austria. 

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Kheiron Medical Technologies' AI-based breast cancer screening software receives CE mark

Kheiron Medical Technologies (Kheiron) has received CE certification for its new artificial intelligence (AI)-based breast screening software, making it the first U.K. company to receive such a designation for deep learning software in radiology.

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Deep learning algorithm detects malignant pulmonary nodules better than radiologists

Researchers have developed a deep learning-based automatic detection algorithm (DLAD) that can detect malignant pulmonary nodules on chest x-rays better than physicians, sharing their findings in a new study published by Radiology.

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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.

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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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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.

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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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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.

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