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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Prostate cancer detection boosted with computer assistance

The addition of computer-aided diagnostic generated MRI series could help radiologists identify clinically significant prostate cancer more frequently. 

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AI software's pediatric fracture detection in line with that of radiologists

An artificial intelligence system that is currently commercially available for use in adults could also have applications in a pediatric population, according to a new study in Pediatric Radiology.

Female Medical Research Scientist Working with Brain Scans

FDA approves AI analysis of high-grade gliomas

An AI startup in the neuro-oncology space has received the government’s go-ahead to market software for analyzing certain fast-growing brain tumors on MRI.

Oncology imaging AI growing fast yet still in its infancy

If generalizable AI models are to meaningfully contribute to precision cancer care, they’ll need to incorporate not only imaging data but also digitalized clinical notes, biomarker assays and monitor readouts.

Radiomics-based models can detect pancreatic cancer well before clinical diagnosis

Recently a radiomics-based machine learning model proved highly accurate at predicting which patients would develop pancreatic cancer three to 36 months after abdominal CT imaging.

Google Cloud intros ambitious branch dedicated to medical imaging

A Big Four tech company has launched a platform it hopes will accelerate data interoperability and AI adoption in, specifically, medical imaging.

AI model uses ECG data to identify new cases of AFib

“Our ultimate goal is to prevent strokes," one Mayo Clinic electrophysiologist said. "I believe the current study has brought us one step closer.”