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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Why AI will make human knowledge more valuable

A recent editorial in STAT argued that as artificial intelligence (AI) continues to proliferate, the need for human providers will not decrease—rather, their knowledge will become more valuable in decision-making.

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Combination of AI, 3D printing software produces detailed organ models

Harvard Medical School researchers in collaboration with 3D bioprinting firm Aether recently introduced a 3D printing software that uses artificial intelligence (AI) to reproduce medical images of organs as 3D models.

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AI has made an impact—but its revolution may not be imminent

Artificial intelligence (AI) continues to change the way radiologists work. The major shift predicted by many isn’t happening as quickly as expected—but AI is reaching areas some didn’t anticipate.

Densitas gains FDA clearance for machine learning software that assesses breast density

Densitas, a medical device company based out of Halifax, Nova Scotia, Canada, announced that DENSITAS|density, its software that uses machine learning to produce breast density reports, has gained FDA clearance.

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Study proposes ‘research framework’ for Alzheimer's based on biomarkers, not symptoms

Current Alzheimer’s disease research is primarily focused on symptoms, but a recent study proposed a new framework for understanding the disease based on biological brain changes and biomarkers.

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What healthcare can learn from Facebook's data scandal

Facebook's most recent data scandal had lawmakers grilling founder and CEO Mark Zuckerberg in a Senate hearing April 11 and presents bioethics lessons for healthcare leaders who are creating AI models for clinical decision making

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An expert's take on the future of machine learning in quantitative image analysis

W. Art Chaovalitwongse, PhD, from the University of Arkansas, discussed using radiomics versus deep learning-based features to predict clinical outcomes from medical imaging data.

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CEO lists 6 reasons radiology will soon be ‘completely revolutionized’ by AI

Elad Walach, founder and CEO of the medical imaging company Aidoc, is one of many in the industry who believes radiology will be transformed by artificial intelligence (AI) sooner rather than later. He went into detail on the topic in a new column published in Forbes.