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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Jefferson Health hit with data breach impacting more than 9,000 patients

The hacker only gained access to billing information and the Philadelphia-based provider began sending out individual notification letters on Jan. 20.

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Radiologists must change their approach to stroke care in the AI era

“Radiologists have an opportunity to situate themselves at the center of patient care, but it will require transforming the operational framework and rebranding ourselves," experts suggested in a new editorial.

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IBM reaches deal to sell Watson Health assets to private equity firm for $1B-plus

Bay Area-based Francisco Partners is picking up the tab, adding several pieces assembled through $4 billion in acquisitions over the years, including Merge Healthcare.

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Machine learning a key tool for limiting clinical, economic impact of C. diff on hospitals

The average treatment cost per case tops $4,000 in the U.S. and increases patients' average hospital stay by 3.6 days.

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6 features of the ideal healthcare artificial intelligence algorithm

Explainability and autonomy are two traits that every AI platform should demonstrate during prospective trials, experts said in PLOS Digital Health.

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The future of medical imaging? Connecting the dots from diagnosis to care

Sponsored by Bayer

What if artificial intelligence (AI) could support doctors in making decisions faster?

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AI drops DBT workloads for radiologists by 40% while also reducing recalls

The model did miss four cancers, prompting one expert to question if radiologists could ever trust a tool knowing it wasn't 100% accurate.

Transparent AI platform shows radiologists its decision-making blueprint for diagnosing breast cancer

“This is what transparency in medical imaging AI could look like and what those in the medical field should be demanding for any radiology challenge,” said a Duke University professor involved in the project.