We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
IBA-Radcal

Download Mobile App




Study Finds AI and Radiologists Achieve Better Results Together

By MedImaging International staff writers
Posted on 25 Oct 2018
A study conducted by researchers from the All India Institutes of Medical Sciences {(AIIMS) New Delhi, India} has found that artificial intelligence (AI) and radiologists working together can achieve better results, helping in case-based decision-making.

Of late, there has been much hype about AI making radiologists redundant. The team of researchers at AIIMS evaluated a simple radiologist-augmented AI workflow to test whether the inclusion of a radiologist’s opinion into an AI algorithm would make the algorithm achieve better accuracy as compared to an algorithm trained on imaging parameters alone. For the study, open-source BI-RADS data sets were evaluated to test whether the inclusion of a radiologist’s opinion (in the form of BI-RADS classification) in addition to image parameters improved the accuracy of prediction of histology using three machine learning algorithms vis-à-vis algorithms using image parameters alone.

According to the study results, the models using the radiologist-provided BI-RADS classification performed significantly better than the models not using them. The researchers concluded that AI and radiologists working together can achieve better results, helping in case-based decision-making. However, further evaluation of the metrics involved in predictor handling by AI algorithms would provide newer insights into imaging, according to the researchers.

Related Links:
All India Institutes of Medical Sciences

Ultrasound-Guided Biopsy & Visualization Tools
Endoscopic Ultrasound (EUS) Guided Devices
Ultrasonic Pocket Doppler
SD1
Ultrasound Needle Guidance System
SonoSite L25
Computed Tomography System
Aquilion ONE / INSIGHT Edition

Channels

Nuclear Medicine

view channel
Image: This artistic representation illustrates how the drug candidate NECT-224 works in the human body (Photo courtesy of HZDR/A. Gruetzner)

Radiopharmaceutical Molecule Marker to Improve Choice of Bladder Cancer Therapies

Targeted cancer therapies only work when tumor cells express the specific molecular structures they are designed to attack. In urothelial carcinoma, a common form of bladder cancer, the cell surface protein... Read more

Imaging IT

view channel
Image: The new Medical Imaging Suite makes healthcare imaging data more accessible, interoperable and useful (Photo courtesy of Google Cloud)

New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible

Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more
Copyright © 2000-2026 Globetech Media. All rights reserved.