33 citations · 66 across the 8 of their papers we have counts for
9 papers
Improving Calibration of Black-Box Radiology AI Using Test-Time Augmentation
Nathan Le, Magdalini Paschali, Arogya Koirala +5
Radiology AI systems increasingly inform clinical decisions such as triage, follow-up imaging, and treatment planning. For these decisions to be made safely, model outputs must be…
MedVAL: Toward Expert-Level Medical Text Validation with Language Models
Asad Aali, Vasiliki Bikia, Maya Varma +24
With the growing use of language models (LMs) in clinical environments, there is an immediate need to evaluate the accuracy and safety of LM-generated medical text. Currently, such…
Automated Structured Radiology Report Generation
Jean-Benoit Delbrouck, Justin Xu, Johannes Moll +11
Automated radiology report generation from chest X-ray (CXR) images has the potential to improve clinical efficiency and reduce radiologists' workload. However, most datasets, incl…
Automated Real-time Assessment of Intracranial Hemorrhage Detection AI Using an Ensembled Monitoring Model (EMM)
Zhongnan Fang, Andrew Johnston, Lina Cheuy +10
Artificial intelligence (AI) tools for radiology are commonly unmonitored once deployed. The lack of real-time case-by-case assessments of AI prediction confidence requires users t…
Evaluating and Improving the Effectiveness of Synthetic Chest X-Rays for Medical Image Analysis
Eva Prakash, Jeya Maria Jose Valanarasu, Zhihong Chen +9
Purpose: To explore best-practice approaches for generating synthetic chest X-ray images and augmenting medical imaging datasets to optimize the performance of deep learning models…
Overview of the First Shared Task on Clinical Text Generation: RRG24 and "Discharge Me!"
Justin Xu, Zhihong Chen, Andrew Johnston +9
Recent developments in natural language generation have tremendous implications for healthcare. For instance, state-of-the-art systems could automate the generation of sections in…
Automated detection of underdiagnosed medical conditions via opportunistic imaging
Asad Aali, Andrew Johnston, Louis Blankemeier +6
Abdominal computed tomography (CT) scans are frequently performed in clinical settings. Opportunistic CT involves repurposing routine CT images to extract diagnostic information an…
Merlin: A Computed Tomography Vision-Language Foundation Model and Dataset
Louis Blankemeier, Ashwin Kumar, Joseph Paul Cohen +37
The large volume of abdominal computed tomography (CT) scans coupled with the shortage of radiologists have intensified the need for automated medical image analysis tools. Previou…
A Vision-Language Foundation Model to Enhance Efficiency of Chest X-ray Interpretation
Zhihong Chen, Maya Varma, Justin Xu +20
Over 1.4 billion chest X-rays (CXRs) are performed annually due to their cost-effectiveness as an initial diagnostic test. This scale of radiological studies provides a significant…