Area of research
Radiology, Nuclear Medicine and Imaging · Pulmonary and Respiratory Medicine
Research interest
Research interests include Radiomics and Machine Learning in Medical Imaging, AI in cancer detection, Digital Radiography and Breast Imaging, and Medical Imaging Techniques and Applications.
FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare
A large-scale multicenter breast cancer DCE-MRI benchmark dataset with expert segmentations
Environment scan of generative AI infrastructure for clinical and translational science
A large-scale multicenter breast cancer DCE-MRI benchmark dataset with expert segmentations.
Enabling global image data sharing in the life sciences.
Summary of the National Cancer Institute 2023 Virtual Workshop on Medical Image De-identification-Part 1: Report of the MIDI Task Group - Best Practices and Recommendations, Tools for Conventional Approaches to De-identification, International Approaches to De-identification, and Industry Panel on Image De-identification.
An Activation Likelihood Estimation Meta-Analysis of Voxel-Based Morphometry Studies of Chemotherapy-Related Brain Volume Changes in Breast Cancer.
New implementation of data standards for AI in oncology: Experience from the EuCanImage project.
Checklist for Artificial Intelligence in Medical Imaging (CLAIM): 2024 Update
Feasibility of regional center telehealth visits utilizing a rural research network in people with Parkinson's disease.
A New Era of Data-Driven Cancer Research and Care: Opportunities and Challenges.
<i>medigan</i>: a Python library of pretrained generative models for medical image synthesis.
Assessment of the Frequency, Phenotypes, and Outcomes of Acute Liver Injury Associated with Amoxicillin/Clavulanate in 1.4 Million Patients in the Veterans Health Administration.
Artificial intelligence and machine learning in cancer imaging
Artificial intelligence and machine learning in cancer imaging.
Feasibility of telemedicine research visits in people with Parkinson's disease residing in medically underserved areas.
Semantic Integration of Multi-Modal Data and Derived Neuroimaging Results Using the Platform for Imaging in Precision Medicine (PRISM) in the Arkansas Imaging Enterprise System (ARIES)
The h-ANN Model: Comprehensive Colonoscopy Concept Compilation Using Combined Contextual Embeddings.
DeIDNER Model: A Neural Network Named Entity Recognition Model for Use in the De-identification of Clinical Notes.
TAX-Corpus: Taxonomy based Annotations for Colonoscopy Evaluation.
The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment.
Role of Machine Learning Techniques to Tackle the COVID-19 Crisis: Systematic Review.
Application of Machine Learning in Intensive Care Unit (ICU) Settings Using MIMIC Dataset: Systematic Review.
A DICOM dataset for evaluation of medical image de-identification.
API Driven On-Demand Participant ID Pseudonymization in Heterogeneous Multi-Study Research.
PRISM: A Platform for Imaging in Precision Medicine
Chest imaging representing a COVID-19 positive rural U.S. population.
DICOM re‐encoding of volumetrically annotated Lung Imaging Database Consortium (LIDC) nodules
Introduction to special issue on datasets hosted in The Cancer Imaging Archive (TCIA)
Quantitative Imaging Informatics for Cancer Research