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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OCT angiography shows promise for diagnosing Alzheimer’s

Clinicians can use optical coherence tomography angiography (OCTA) to noninvasively diagnose patients with early cognitive impairment, an early indicator of Alzheimer’s disease (AD), reported authors of a single-center study published in PLOS One.

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New ACR software platform allows radiologists to create, validate, use AI

The American College of Radiology (ACR) Data Science Institute (DSI) has launched ACR AI-LAB, a new software platform that helps radiologists create, validate and use artificial intelligence to treat patients.

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4 challenges machine learning must overcome to help clinicians

Machine learning has the potential to reshape the patient-doctor relationship, according to a new review published in the New England Journal of Medicine, but it must overcome a few challenges first.

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Deep learning model only needs a single breast MR image to assess cancer risk

A new AI model can accurately determine a patient’s five-year cancer risk based on a single breast MR image, outperforming state-of-the art risk assessment models.

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Deep learning bests radiologists at classifying thoracic disease on chest x-rays

The algorithm was externally validated on 486 normal chest radiographs and 529 abnormal chest radiographs taken from four different institutions across multiple continents.

FDA working on new steps for regulating AI devices

The FDA announced Tuesday, April 3, that it is working on a new framework to regulate AI-based medical devices that continually learn from healthcare data.

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FDA developing framework for AI-based medical devices that ‘learn’ in real time

The FDA has announced that it is working toward developing a new regulatory framework for medical devices that use advanced artificial intelligence (AI) algorithms.

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Deep learning improves tumor contouring, may help patients with head and neck cancer

“Our findings show that AI-assistance can effectively improve contouring accuracy and reduce intra- and interobserver variation and contouring time, which could have a positive impact on tumor control and patient survival,” wrote authors of a recent study published in Radiology.

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