Using artificial intelligence to improve cancer diagnosis and treatment
Official title: Large-scale artificial intelligence using radiomics, deep learning, and physics-based generative modeling to improve clinical outcomes in nuclear medicine
Funded at Johns Hopkins University · NIH-11006317 · Data updated 2026-11-12
This study is working on using smart computer technology to help doctors find and treat cancer earlier and more accurately, so patients can get better care and outcomes.
Quick facts
| Grant type | Career grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Johns Hopkins University NIH-funded |
| Lab location | 1 site (Baltimore, United States) |
| Project start | January 4, 2024 |
| Project end | December 31, 2025 |
| Funding year | 2025 |
| Award (this year) | $170,100 |
| NIH project number | 5K99CA287045-02 |
| Project ID | NIH-11006317 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals diagnosed with various types of cancer who require imaging for diagnosis and treatment planning.
✕Less likely to help
Patients with non-cancerous conditions or those who do not require imaging studies may not benefit from this research.
What this research studies
This research focuses on developing advanced artificial intelligence (AI) and deep learning (DL) techniques to enhance the early detection and treatment of cancer. By analyzing radiological data, the project aims to extract valuable information that can lead to better diagnosis and prognosis of malignant diseases. The study addresses challenges in traditional radiomics by utilizing large datasets and improving the reproducibility of results, ultimately aiming to create effective tools for nuclear medicine. Patients may benefit from more accurate and timely cancer treatments as a result of these innovations.
Why it matters
Potential benefit: If successful, this research could lead to earlier and more accurate cancer diagnoses, improving treatment outcomes for patients.
How similar studies have gone: Other research has shown promising results using AI and deep learning in cancer imaging, indicating that this approach has the potential for significant advancements.
Where this research is happening
-
Johns Hopkins University
Baltimore, United States Active
Researchers
- Principal investigator: Leung, Kevin Ho-Yin — Johns Hopkins University
- Study coordinator: Leung, Kevin Ho-Yin
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.