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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Tech firm, specializing in tools to enhance MR imaging, ups fundraising total to $140M

Perspectum's flagship product is a noninvasive AI tool used to help physicians evaluate for the signs of liver disease. 

QTrobot (left) and Misty. Photos by Hatice Gunes/University of Cambridge.

Toylike robot pleases counseling clients where humanoid counterpart struggles to connect

When human counselors are unavailable to provide work-based wellness coaching, robots can substitute—as long as the workers are comfortable with emerging technologies and the machines aren’t overly humanlike.

Google ups activity in 4 reaches of healthcare AI

Along with expanding research into large-language models to rival OpenAI’s ChatGPC, the search-engine king is working on AI for improving maternal care, ultrasound access and tuberculosis screening.

To juice medical AI adoption, try a little Aristotelian persuasion

Wary consumers can be convinced to allow AI into their healthcare habits by communications campaigns tuned to the ancient rhetorical categories of ethos, pathos and logos. 

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More experts weigh in on the use of ChatGPT in radiology: Ethical use is ‘imperative’

"It is essential for the radiologist to check and verify the generated report," one member of the specialty wrote Tuesday in Radiology

Ulcerative colitis AI identifies activity vs. remission, predicts future flareups

Researchers across the pond have developed and externally validated an AI model that can predict flareups of ulcerative colitis. 

Commercially available AI tool could reduce radiologist workloads by 10% or more

The tool’s sensitivity was recorded as 99.1% for abnormal radiographs and 99.8% for critical radiographs—better than two board-certified radiologists who also interpreted the exams. 

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Artificial intelligence bests ED docs, but not experienced radiologists, at detecting fractures

“This study suggests that deep learning algorithms can be useful in improving the detection of fractures," experts wrote Monday in Pediatric Radiology