[HTML][HTML] Ability of ChatGPT to generate competent radiology reports for distal radius fracture by use of RSNA template items and integrated AO classifier
WA Bosbach, JF Senge, B Nemeth, SH Omar… - Current problems in …, 2024 - Elsevier
The amount of acquired radiology imaging studies grows worldwide at a rapid pace. Novel
information technology tools for radiologists promise an increase of reporting quality and as …
information technology tools for radiologists promise an increase of reporting quality and as …
Creation and validation of a chest X-ray dataset with eye-tracking and report dictation for AI development
We developed a rich dataset of Chest X-Ray (CXR) images to assist investigators in artificial
intelligence. The data were collected using an eye-tracking system while a radiologist …
intelligence. The data were collected using an eye-tracking system while a radiologist …
Cross-modal clinical graph transformer for ophthalmic report generation
Automatic generation of ophthalmic reports using data-driven neural networks has great
potential in clinical practice. When writing a report, ophthalmologists make inferences with …
potential in clinical practice. When writing a report, ophthalmologists make inferences with …
Chest imagenome dataset for clinical reasoning
Despite the progress in automatic detection of radiologic findings from chest X-ray (CXR)
images in recent years, a quantitative evaluation of the explainability of these models is …
images in recent years, a quantitative evaluation of the explainability of these models is …
AnaXNet: anatomy aware multi-label finding classification in chest X-ray
Radiologists usually observe anatomical regions of chest X-ray images as well as the
overall image before making a decision. However, most existing deep learning models only …
overall image before making a decision. However, most existing deep learning models only …
Attribute prototype-guided iterative scene graph for explainable radiology report generation
The potential of automated radiology report generation in alleviating the time-consuming
tasks of radiologists is increasingly being recognized in medical practice. Existing report …
tasks of radiologists is increasingly being recognized in medical practice. Existing report …
CheXRelNet: An Anatomy-Aware Model for Tracking Longitudinal Relationships Between Chest X-Rays
Despite the progress in utilizing deep learning to automate chest radiograph interpretation
and disease diagnosis tasks, change between sequential Chest X-rays (CXRs) has received …
and disease diagnosis tasks, change between sequential Chest X-rays (CXRs) has received …
Curation of the candid-ptx dataset with free-text reports
S Feng, D Azzollini, JS Kim, CK **… - Radiology: Artificial …, 2021 - pubs.rsna.org
Curation of the CANDID-PTX Dataset with Free-Text Reports | Radiology: Artificial
Intelligence RSNA "skipMainNavigation" closeDrawerMenuopenDrawerMenu Home …
Intelligence RSNA "skipMainNavigation" closeDrawerMenuopenDrawerMenu Home …
A proposed framework for machine learning-aided triage in public specialty ophthalmology clinics in Hong Kong
The public specialty ophthalmic clinics in Hong Kong, under the Hospital Authority, receive
tens of thousands of referrals each year. Triaging these referrals incurs a significant …
tens of thousands of referrals each year. Triaging these referrals incurs a significant …
Hierarchical Vision Transformers for Disease Progression Detection in Chest X-Ray Images
Chest radiography is a commonly used diagnostic imaging exam for monitoring disease
progression and treatment effectiveness. While machine learning has made significant …
progression and treatment effectiveness. While machine learning has made significant …