3 citations · 5 across the 4 of their papers we have counts for
4 papers
Deep Learning-based Prediction of Breast Cancer Tumor and Immune Phenotypes from Histopathology
Tiago Gonçalves, Dagoberto Pulido-Arias, Julian Willett +8
The interactions between tumor cells and the tumor microenvironment (TME) dictate therapeutic efficacy of radiation and many systemic therapies in breast cancer. However, to date,…
PRECISE Framework: GPT-based Text For Improved Readability, Reliability, and Understandability of Radiology Reports For Patient-Centered Care
Satvik Tripathi, Liam Mutter, Meghana Muppuri +8
This study introduces and evaluates the PRECISE framework, utilizing OpenAI's GPT-4 to enhance patient engagement by providing clearer and more accessible chest X-ray reports at a…
Enrichment of the NLST and NSCLC-Radiomics computed tomography collections with AI-derived annotations
Deepa Krishnaswamy, Dennis Bontempi, Vamsi Thiriveedhi +6
Public imaging datasets are critical for the development and evaluation of automated tools in cancer imaging. Unfortunately, many do not include annotations or image-derived featur…
A generalized framework to predict continuous scores from medical ordinal labels
Katharina V. Hoebel, Andreanne Lemay, John Peter Campbell +7
Many variables of interest in clinical medicine, like disease severity, are recorded using discrete ordinal categories such as normal/mild/moderate/severe. These labels are used to…