Area of research
Radiology, Nuclear Medicine and Imaging · Health Informatics
Research interest
Research interests include Radiology practices and education, Radiomics and Machine Learning in Medical Imaging, Artificial Intelligence in Healthcare and Education, and Topic Modeling.
Merlin: a computed tomography vision-language foundation model and dataset.
A multimodal retinal aging clock for biological age prediction and systemic health assessment via OCT and fundus imaging
Shaping the future of myopia: artificial intelligence for vitreoretinal complications of high and pathologic myopia
A generalizable deep learning system for cardiac MRI.
Effects of Real-Time Notification of AI-Detected Incidental Coronary Artery Calcium on Statin Prescription: The NOTIFY-PICTURE Trial.
AI for Clinical Applications
FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare
A vision-language foundation model for the generation of realistic chest X-ray images.
Generative artificial intelligence in medicine
Foundation Models in Radiology: What, How, Why, and Why Not.
A clinically accessible small multimodal radiology model and evaluation metric for chest X-ray findings
Open-Source Large Language Models in Radiology: A Review and Tutorial for Practical Research and Clinical Deployment.
Crucial Role of Understanding in Human-Artificial Intelligence Interaction for Successful Clinical Adoption.
Best Practices for Large Language Models in Radiology.
Framework for Environmentally Sustainable Radiology: Call for Collaborative Action and a Health-Centered Focus.
Generative artificial intelligence in medicine.
A clinically accessible small multimodal radiology model and evaluation metric for chest X-ray findings.
Leveraging large language models to extract smoking history from clinical notes for lung cancer surveillance
Ocular Biometry OCR: a machine learning algorithm leveraging optical character recognition to extract intra ocular lens biometry measurements
Oncoshare-Lung: Novel three-way linkage of neighboring academic and community medical centers to state cancer registry for lung cancer.
RadGPT: A System Based on a Large Language Model That Generates Sets of Patient-Centered Materials to Explain Radiology Report Information.
A Dataset for Understanding Radiologist-Artificial Intelligence Collaboration.
Automatic Abstraction of Computed Tomography Imaging Indication Using Natural Language Processing for Evaluation of Surveillance Patterns in Long-Term Lung Cancer Survivors.
Expert-level validation of AI-generated medical text with scalable language models
The Effect of AI on the Radiologist Workforce: A Task-Based Analysis
A Dataset for Understanding Radiologist-Artificial Intelligence Collaboration
EchoGraph System for Automated Quality Assessment of Echocardiography Reports
Enabling national identification of lung cancer screening eligibility with large language models.
PT1.01.01 Large Language Models to Extract Smoking History From Clinical Notes in EHR to Evaluate Lung Cancer Surveillance Strategies
Deep Learning Algorithm Prognosticating Retinal Tears and Detachments From Optical Coherence Tomography