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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Philips launches first global start-up collaboration program focused on the application of artificial intelligence in healthcare

2-week program gives 19 artificial intelligence start-up companies access to Philips’ health technology expertise and its ecosystem of knowledge partners

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AI measures breast density as accurately as experienced mammographers

Breast imagers and artificial intelligence (AI) experts have shown that a new AI algorithm measures breast density with accuracy comparable to an experienced breast imager, according to new research published online Oct. 16 in Radiology.

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Mixed-reality headset enhances accuracy of external ventricular drain insertion

Using a mixed-reality holographic computer headset, neurosurgeons can more accurately perform external ventricular drain (EVD) insertion, according a new study out of Beijing published in the Journal of Neurosurgery.

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UCLA’s William Hsu named deputy editor of RSNA's new AI journal

William Hsu, PhD, a biomedical informatician and associate professor of radiology at UCLA, has been named deputy editor for the Radiological Society of North America (RSNA)’s new journal, Radiology: Artificial Intelligence.

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AI improves with input from radiologists

Artificial intelligence (AI) models utilizing radiologist-provided BI-RADS classification outperformed methods that did not use them, according to an Oct. 15 study in the Journal of the American College of Radiology.

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Microscopic imaging of kidney damage from contrast dyes opens door for novel drug therapies

Using microscopic imaging, researchers from the University of Calgary in Alberta, Canada have shown how the kidneys negatively respond to contrast dyes used during various medical tests and procedures, according to a university press release published Oct. 15.

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Novel AI approach can help radiologists improve osteoarthritis x-ray diagnosis

A novel convolutional neural network (CNN) approach could be used to help radiologists improve their classification of osteoarthritis (OA) on knee radiographs, reported authors of a new study published in the Journal of Digital Imaging.

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AI accurately distinguishes between false-positive, malignant, negative mammograms

Deep learning may accurately identify false-positive mammograms and distinguish such from images identified as malignant or negative, according to new research published Oct. 11 in the journal Clinical Cancer Research.

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Around the web

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GE HealthCare launches new cardiac CT scanner with advanced AI capabilities

GE HealthCare designed the new-look Revolution Vibe CT scanner to help hospitals and health systems embrace CCTA and improve overall efficiency.

Cardiovascular Business
Bracco updates HeartSee coronary flow capacity software with new diagnostic features

Clinicians have been using HeartSee to diagnose and treat coronary artery disease since the technology first debuted back in 2018. These latest updates, set to roll out to existing users, are designed to improve diagnostic performance and user access.

Cardiovascular Business
Key trends in diagnostic heart testing: CT on the rise as some traditional techniques fall out of favor

The cardiac technologies clinicians use for CVD evaluations have changed significantly in recent years, according to a new analysis of CMS data. While some modalities are on the rise, others are being utilized much less than ever before.