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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Radiologist-backed software startup Sirona Medical acquiring assets, personnel from AI firm Nines

The deal includes Nines' data pipeline, machine learning engines, analytics tools, and two U.S. Food and Drug Administration-cleared products. 

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Automated CT scoring system accurately predicts prognosis in stroke patients

The study used non-contrast CT and CT perfusion imaging to analyze agreement between an automated reader and human radiologists with differing experience levels.

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MindMaze secures $105 million to expand commercial growth

The financing was led by Concord Health Partners in conjunction with AlbaCore Capital Group and London-based Hambro Perks.

Legal ramifications to consider when integrating AI into daily radiology practice

“Formidable legal obstacles threaten AI’s impact on the specialty and, if unchanged, have the potential to preclude the future success of this emerging industry,” experts cautioned in AJR.

Coronary CT AI firm HeartFlow scraps $2.4B merger deal, citing ‘unfavorable market conditions’

Hedge fund investors and the Redwood City, California, vendor considered adjusting the sale price, but opted to terminate the deal instead.

Why radiologist virtue is so important in the AI era: 6 pieces of advice

“In the end, no matter how smart the machines are with their algorithms and mysterious black boxes, they are no match for human virtue when it comes to preserving patient trust and the survival of the profession,” one expert said in AJR.

breast cancer screening mammography

Combining neural network with breast density measurements boosts interval cancer detection rates

With up to 30% of breast cancers developing in between screenings, there is a great need to improve risk assessments, experts discussed recently in Radiology.

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Carestream scores FDA clearance for tool to reduce radiation dosage during imaging

The artificial intelligence-powered product could prove valuable during neonatal and pediatric exams, leaders said.