Area of research
Pulmonary and Respiratory Medicine · Radiology, Nuclear Medicine and Imaging
Research interest
Research interests include Radiomics and Machine Learning in Medical Imaging, Lung Cancer Diagnosis and Treatment, Occupational and environmental lung diseases, and Pleural and Pulmonary Diseases.
Artificial intelligence in medicine: mitigating risks and maximizing benefits via quality assurance, quality control, and acceptance testing
AI and machine learning in medical imaging: key points from development to translation
A Competition, Benchmark, Code, and Data for Using Artificial Intelligence to Detect Lesions in Digital Breast Tomosynthesis
AI in medical imaging grand challenges: translation from competition to research benefit and patient care
Germline Variants Incidentally Detected via Tumor-Only Genomic Profiling of Patients With Mesothelioma
AAPM task group report 273: Recommendations on best practices for AI and machine learning for computer‐aided diagnosis in medical imaging
Considerations for Imaging of Malignant Pleural Mesothelioma: A Consensus Statement from the International Mesothelioma Interest Group
Emphysema Detection in the Course of Lung Cancer Screening: Optimizing a Rare Opportunity to Impact Population Health
Deep learning-based segmentation of malignant pleural mesothelioma tumor on computed tomography scans: application to scans demonstrating pleural effusion
Effects of variability in radiomics software packages on classifying patients with radiation pneumonitis
Harmonization of radiomic feature variability resulting from differences in CT image acquisition and reconstruction: assessment in a cadaveric liver
EURACAN/IASLC Proposals for Updating the Histologic Classification of Pleural Mesothelioma: Towards a More Multidisciplinary Approach
Critical Challenges to the Management of Clinical Trial Imaging: Recommendations for the Conduct of Imaging at Investigational Sites
Autosegmentation for thoracic radiation treatment planning: A grand challenge at AAPM 2017
PROSTATEx Challenges for computerized classification of prostate lesions from multiparametric magnetic resonance images
Revised Modified Response Evaluation Criteria in Solid Tumors for Assessment of Response in Malignant Pleural Mesothelioma (Version 1.1)
Variation in algorithm implementation across radiomics software
Incorporation of pre-therapy <sup>18</sup>F-FDG uptake data with CT texture features into a radiomics model for radiation pneumonitis diagnosis
Three‐dimensional image analysis for staging chronic rhinosinusitis
Quality assurance and quantitative imaging biomarkers in low-dose CT lung cancer screening
LUNGx Challenge for computerized lung nodule classification
A Multicenter Study of Volumetric Computed Tomography for Staging Malignant Pleural Mesothelioma
North American Multicenter Volumetric CT Study for Clinical Staging of Malignant Pleural Mesothelioma: Feasibility and Logistics of Setting Up a Quantitative Imaging Study
Imaging in pleural mesothelioma: A review of the 13th International Conference of the International Mesothelioma Interest Group
Lung Texture in Serial Thoracic Computed Tomography Scans: Correlation of Radiomics-based Features With Radiation Therapy Dose and Radiation Pneumonitis Development
Guest Editorial: LUNGx Challenge for computerized lung nodule classification: reflections and lessons learned
Computer‐assisted staging of chronic rhinosinusitis correlates with symptoms
Role of the Quantitative Imaging Biomarker Alliance in Optimizing CT for the Evaluation of Lung Cancer Screen–Detected Nodules
CT-Based Pulmonary Artery Measurements for the Assessment of Pulmonary Hypertension
Observer Variability in Mesothelioma Tumor Thickness Measurements: Defining Minimally Measurable Lesions