Imaging Informatics: Page 49

AI model generates x-ray reports similar to radiologists
By Will Morton
A team at Northwestern University has developed an AI model that could serve to alert physicians to life-threatening diseases on chest x-rays.
October 5, 2023
The AI model is an encoder-decoder model trained to generate a text report given a chest x-ray and most recent comparison (anterior-posterior or posterior-anterior view only). The vision encoder weights were initialized from Vision Transformer (ViT) base and the text decoder weights were initialized from Robustly Optimized BERT Pretraining Approach (RoBERTa) base before training for 30 epochs on a data set of 900,000 chest x-rays (CXRs). cp indicates chest pain; sob = shortness of breath. Image courtesy of JAMA Open Network.
'Timika score' on x-rays may help identify complex TB cases
By Will Morton
Machine learning has revealed new potential for a simple clinical tool proposed in 2010 for diagnosing tuberculosis (TB) on x-rays.
October 4, 2023
Tuberculosis
Deep learning comparable to radiologists for ultrasonic liver analysis
By Amerigo Allegretto
Deep learning is on par with radiologists when it comes to ultrasonic detection and grading of hepatic steatosis.
October 4, 2023
Liver Digital Tablet 400
How effective is AI for detecting PE on CTPA studies?
By Kate Madden Yee
The use of an AI triage system to detect any pulmonary embolism (PE) on CT pulmonary angiography (CTPA) studies decreases patient wait times, but it doesn't improve radiologist accuracy, miss rate, or exam and report turnaround times.
October 4, 2023
Pulmonary Embolism Illustration 400
Can transformer models improve AI image interpretations?
By Will Morton
A new class of AI appears to move the technology closer to what radiologists are capable of when they interpret chest x-rays.
October 3, 2023
Representative radiographs (top), acquired in anteroposterior projection in the supine position, and corresponding attention maps (bottom). (A) Images show main diagnostic findings of the internal data set in a 49-year-old male patient with congestion, pneumonic infiltrates, and effusion (left); a 64-year-old male patient with congestion, pneumonic infiltrates, and effusion (middle); and a 69-year-old female patient with effusion (right). Image courtesy of Radiology.
Deep learning helps categorize acute appendicitis on pelvic CT
By Kate Madden Yee
A combined deep learning and radiomics model helps clinicians differentiate complicated from uncomplicated acute appendicitis on pelvic CT.
September 29, 2023
Appendix Blue 400
Nanox touts CT study using its AI software
By AuntMinnie.com staff writers
Nanox Imaging said that a study in Israel using CT scans and its HealthCCSng AI algorithm identified moderate to severe levels of coronary artery calcium in 58% of patients.
September 29, 2023
Artificial Intelligence Ai Abstract 400
Sirona inks deals with AI developers
By AuntMinnie.com staff writers
Sirona Medical has established partnerships with AI developers Koios and RevealDX. ahead of its launch of its new open developer ecosystem Amplify SDK.
September 28, 2023
Ai Hand
Louis Plesner talks AI x-ray exam reads vs. radiologists'
By Will Morton
In an interview with AuntMinnie.com, Louis Plesner, MD, discussed a study he led that found radiologists outperformed four commercially available algorithms for identifying diseases on chest x-rays.
September 28, 2023
2023 09 28 Plesner Interview V2
Chest x-ray model analysis reveals race and sex bias
By Will Morton
An AI chest x-ray "foundation model" developed by Google researchers has demonstrated racial and sex-related bias leading to uneven performance.
September 27, 2023
Ai Bias
Radiologists outperform chest x-ray AI
By Will Morton
Radiologists outperformed four commercially available AI algorithms when diagnosing lung diseases on chest x-rays.
September 26, 2023
A representative posteroanterior chest x-ray (A) in a 71-year-old male patient who underwent examination due to progression of dyspnea shows bilateral fibrosis (arrows), which was misclassified as airspace disease by all four AI tools. Image courtesy of Radiology.
PET radiomics model identifies high-risk lymphoma patients
By Will Morton
A group in the Netherlands has built a radiomics model using FDG-PET scans that predicts disease-free survival odds in patients with relapsed lymphoma.
September 25, 2023
Lymphoma Scan
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