A5022667218- Radiomics and Machine Learning in Medical Imaging
- Artificial Intelligence in Healthcare and Education
- AI in cancer detection
- Advanced X-ray and CT Imaging
- Lung Cancer Diagnosis and Treatment
- Hepatocellular Carcinoma Treatment and Prognosis
- Multiple and Secondary Primary Cancers
- Radiology practices and education
- Cancer Immunotherapy and Biomarkers
- Surgical Simulation and Training
- Cholangiocarcinoma and Gallbladder Cancer Studies
- Traumatic Brain Injury and Neurovascular Disturbances
- MRI in cancer diagnosis
- Plant Surface Properties and Treatments
- Clinical Reasoning and Diagnostic Skills
- Medical Imaging and Analysis
- Medical Imaging Techniques and Applications
- Pesticide Residue Analysis and Safety
- Colorectal Cancer Treatments and Studies
- Gastric Cancer Management and Outcomes
- Liver Disease and Transplantation
- Renal cell carcinoma treatment
- Renal and related cancers
- Breast Cancer Treatment Studies
- Sarcoma Diagnosis and Treatment
University of California, Irvine Medical Center
2024
Kaiser Permanente
2024
Columbia University
2019-2024
University of California, Irvine
2024
New York Hospital Queens
2020-2022
Columbia University Irving Medical Center
2020-2022
NewYork–Presbyterian Hospital
2020-2022
Texas Health Dallas
2022
Knowles (United States)
1996
Augmented reality (AR) guidance holds potential to improve transcatheter interventions by enabling visualization of and interaction with patient-specific 3-dimensional virtual content. Positioning cerebral embolic protection devices (CEP) during aortic valve replacement (TAVR) increases patient exposure radiation iodinated contrast, procedure time. AR may enhance procedural facilitate a safer intervention.
Background The burgeoning interest in ChatGPT as a potentially useful tool medicine highlights the necessity for systematic evaluation of its capabilities and limitations. Purpose To evaluate accuracy, reliability, repeatability differential diagnoses produced by from transcribed radiologic findings. Materials Methods Cases selected radiology textbook series spanning variety imaging modalities, subspecialties, anatomic pathologies were converted into standardized prompts that entered...
We investigated the performance of multiple radiomics feature extractors/software on predicting epidermal growth factor receptor mutation status in 228 patients with non-small cell lung cancer from publicly available data sets The Cancer Imaging Archive. imaging and clinical were split into training (n = 105) validation cohorts 123). Two most cited open-source extractors, IBEX (1563 features) Pyradiomics (1319 features), our in-house software, Columbia Image Feature Extractor (CIFE) (1160...
Many AR and VR task domains involve manipulating virtual objects; for example, to perform 3D geometric transformations. These operations are typically accomplished with tracked hands or hand-held controllers. However, there some activities in which the user's already busy another task, requiring user temporarily stop what they doing second while also taking time disengage reengage original (e.g., putting down picking up tools). To avoid need overload this way an system guiding a physician...
We propose a novel framework for determining radiomics feature robustness by considering the effects of both biological and noise signals. This is preliminarily tested in study predicting epidermal growth factor receptor (EGFR) mutation status non-small cell lung cancer (NSCLC) patients. Pairs CT images (baseline, 3-week post therapy) 46 NSCLC patients with known EGFR were collected FDA-customized anthropomorphic thoracic phantom was scanned on two vendors’ scanners at four different tube...
Achieving high feature reproducibility while preserving biological information is one of the main challenges for generalizability current radiomics studies. Non-clinical imaging variables, such as reconstruction kernels, have shown to significantly impact features. In this study, we retrain an open-source convolutional neural network (CNN) harmonize computerized tomography (CT) images with various kernels improve and radiomic model performance using epidermal growth factor receptor (EGFR)...
// Shawn Sun 1 , Florent L. Besson 2 Binsheng Zhao Lawrence H. Schwartz and Laurent Dercle Department of Radiology, New York Presbyterian Hospital, Columbia University Medical Center, York, USA Biophysics, Nuclear Medicine-Molécular Imaging, Hôpitaux Universitaires Paris-Saclay, AP-HP, Université Paris Saclay/CEA/CNRS/Inserm/BioMaps, France Correspondence to: Dercle, email: ld2752@cumc.columbia.edu Keywords: positron emission tomography; computed prognosis; lung cancer;...