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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IBM Watson, Guerbet to develop AI imaging tool to help liver cancer diagnostics

IBM Watson Health and medical imaging contrast agent company Guerbet have entered a strategic partnership to develop artificial intelligence (AI) software to support liver cancer diagnostics and care by utilizing CT and MRI technology.

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Guerbet, IBM Watson Health collaborating on AI-based liver cancer solutions

Guerbet announced Tuesday, July 10, that it has signed an exclusive agreement to collaborate with IBM Watson Health and develop artificial intelligence (AI) software solutions that help detect, diagnose and treat liver cancer.

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Helping hands: Widening access to focused ultrasound in US reduces essential tremors

A Pennsylvania farmer suffering from essential tremors in both hands recalled how his experience undergoing focused ultrasound treatment was risky but ultimately worth it, according to a July 9 article by NPR.

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ACR Data Science Institute begins releasing AI use cases for industry feedback

The American College of Radiology Data Science Institute (ACR DSI), which first launched in May 2017, has started releasing use cases from its TOUCH-AI library for industry feedback. A final release is scheduled for later this year.

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Texas center reduces radiation targeting variability with deep learning

A deep learning algorithm deployed at MD Anderson Cancer Center in Houston successfully automated and standardized clinical target volumes (CTVs) for radiation therapy in head and neck cancer patients.

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ACR DSI releases 1st AI use cases seeking feedback

The American College of Radiology Data Science Institute (ACR DSI) released its first use cases from the TOUCH-AI library for industry comment in order to gain feedback before it releases the entire library this fall, according to an ACR release.

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Digital pathology technique 90% accurate in counting T-cells

A team from Finland has developed an artificial intelligence (AI) pathology model that detected the T-cell count in cancerous tissue with 90 percent accuracy.

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Johns Hopkins AI, machine learning image analysis may reduce risk of blindness

Johns Hopkins University researchers have developed image analysis and machine learning tools to detect age-related macular degeneration (AMD), according to a study published in the May 2018 issue of Nature Medicine.