In December, I participated in an inspiring Innovation Lab hosted by the NIH and NCI, uniting diverse experts to explore how quantum computing can tackle complex biomedical challenges. My team, Quantum Heart, won a $25,000 prize for our innovative project. This experience fostered optimism and strong connections for future breakthroughs in medicine.
Category Archives: Research
Empowering Cancer Care with AI: A Jefferson Medical Student–Led Innovation
I’m excited to share a new collaborative study I had the privilege of co-authoring, which was recently published in Nutrients. Led by Jefferson medical student Julia Logan, this work explores how large language models (LLMs) like ChatGPT and Gemini can deliver accessible, culturally sensitive dietary advice to cancer patients—many of whom lack access to professionalContinue reading “Empowering Cancer Care with AI: A Jefferson Medical Student–Led Innovation”
AI-Powered Auto-Segmentation in Liver Cancer Therapy
We’re excited to share our latest work published in Technology in Cancer Research & Treatment: “Deep Learning-Based Auto-Segmentation for Liver Yttrium-90 Selective Internal Radiation Therapy” — a collaboration between Jun Li, Rani Anne, and myself. This study introduces a deep learning (DL) model built on the 3D U-Net architecture, developed to automatically segment the liverContinue reading “AI-Powered Auto-Segmentation in Liver Cancer Therapy”
The Nexus featured our cardiac PET radiomics study
Jefferson investigates the relationship between Artificial Intelligence and Heart Disease in “The Nexus”.
Shining a Light: Unveiling Cardiac Risks Using PET Imaging in Lung Cancer Radiotherapy
A study on cardiac toxicity in lung cancer treatment is highlighted in a JCO CCI editorial. The findings could significantly impact patient care. The study focuses on using Positron Emission Tomography Imaging in lung cancer radiotherapy to reveal cardiac risks. #CardiacToxicity #LungCancer #Innovation
Exploring published and novel pre-treatment CT and PET radiomics to stratify risk of progression among early-stage non-small cell lung cancer patients treated with stereotactic radiation
Maria Thor 1,4, Kelly Fitzgerald 2,4, Aditya Apte 1, Jung Hun Oh 1, Aditi Iyer 1, Otasowie Odiase 2, Saad Nadeem 1, Ellen D. Yorke 1, Jamie Chaft 3, Abraham J. Wu 2, Michael Offin 3, Charles B Simone II 2, Isabel Preeshagul 3, Daphna Y. Gelblum 2, Daniel Gomez 2, Joseph O. Deasy 1,Continue reading “Exploring published and novel pre-treatment CT and PET radiomics to stratify risk of progression among early-stage non-small cell lung cancer patients treated with stereotactic radiation”
Deep Learning Segmentation for Accurate GTV and OAR Segmentation in MR-Guided Adaptive Radiotherapy for Pancreatic Cancer Patients
This content does not provide sufficient information to create a concise summary. It mentions AAPM 2023 and ASTRO 2023, which appear to be future events, and provides links to slideshare presentations, but no detailed information or context is given.
Novel Functional Radiomics for Predicting Cardiotoxicity in Lung Cancer Radiotherapy using Cardiac FDG-PET Uptake
The provided content discusses functional Delta-Radiomics and its application in predicting overall survival, showcased through a Slideshare presentation. Additionally, there is mention of a study on the classification of cardiac uptake patterns, also presented on Slideshare, using functional Radiomics.
2023 Accepted/Invited Annual Meeting abstracts
Longitudinal CBCT radiomics in Lung Cancer supported by Varian Medical Systems Inc.
Jefferson Whole Lung CBCT radiomics
Qualia Radiomics 