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. 

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.”

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The lack of clinical trials may be holding back AI adoption in healthcare

The healthcare industry has a lot of hope for machine learning solutions across patient care. However, there are many barriers to widespread adoption keeping machine learning from being implemented into clinical practice.

Monique Rasband from KLAS Research shares trends in PACS and radiology informatics.

VIDEO: 6 key trends in PACS and radiology informatics observed by KLAS

Monique Rasband, vice president of imaging, cardiology and oncology, KLAS Research, shares some of technology trends observed in radiology PACS and and imaging informatics since 2019.