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A research collaboration among Columbia's women in radiology directly addresses the pandemic's negative effect on women who conduct biomedical research.
Biomedical engineer and professor of radiology is honored for her leadership and innovation in ultrasound imaging and therapeutics in medical practice and treatment.
The annual award supports the preliminary pilot phase of a scientific project with a focus on head and neck imaging.
- June 11, 2021
Pediatric radiologist Diego Jaramillo, MD, MPH is using a novel, MRI-based technique to predict growth in children.
- April 16, 2021
Congratulations to Dr. Diego Jaramillo who has secured a five-year R01 grant for his project, “Understanding Skeletal Growth Using Diffusion Tensor Imaging of the Physis and Metaphysis”.
Source:Frontiers in OncologyMarch 29, 2021
A review article looks at the challenges facing the translation of developed radiomics signatures from bench to bedside, progress made to date, and potential strategies to reduce feature variability.
- November 18, 2020
Thoracic radiologist Mary Salvatore, MD is looking at cancers of the lung that occur with fibrosis.
- October 15, 2020
This Breast Cancer Awareness Month, we talked to Dr. Richard Ha about his research and how artificial intelligence is changing the future of breast cancer screening.
- July 22, 2020
A short animation explains radiomics and how it how it has been used by scientists to successfully assess the efficacy of cancer treatment.
- July 21, 2020
Scientists from the Department of Radiology are using artificial intelligence to extract information from standard-of-care CT scans that has potential to individually assess cancer treatments.
Source:Health ImagingJuly 8, 2020
An artificial intelligence platform developed by scientists at Columbia Radiology performed well at differentiating between radiographs with and without fractures.
Source:American Association for Cancer ResearchMarch 20, 2020
In a new study from Columbia Radiology, researchers utilized artificial intelligence (AI) to train algorithms to predict tumor sensitivity to three systemic cancer therapies.