Improving Care for Advanced Cancer Using Smart Technology
Official title: Human-Machine Collaborations to Improve Prognosis and Clinical Decision-Making in Advanced Cancer
Funded at Emory University · NIH-11123903 · Data updated 2026-11-12
This project helps doctors better understand the future health of advanced cancer patients by combining their expertise with smart computer programs, aiming for earlier and better care planning.
Quick facts
| Grant type | Career grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Emory University NIH-funded |
| Lab location | 1 site (Atlanta, United States) |
| Project start | July 5, 2021 |
| Project end | June 30, 2026 |
| Funding year | 2025 |
| Award (this year) | $231,225 |
| NIH project number | 5K08CA263541-06 |
| Project ID | NIH-11123903 on NIH RePORTER |
Who could benefit from this research
✓Could help
This research is relevant to patients diagnosed with advanced cancer and their caregivers.
✕Less likely to help
Patients who do not have advanced cancer or are not seeking advance care planning may not directly benefit from this specific research.
What this research studies
For patients with advanced cancer, it can be hard for doctors to accurately predict how their illness will progress, which can delay important conversations about future care. This project aims to help doctors make more accurate predictions by giving them tools that combine their own knowledge with insights from computer programs that analyze health records. The goal is to ensure that patients and their families can have important discussions about their care earlier, leading to more personalized and supportive treatment plans. This approach could help patients receive the right kind of care at the right time, improving their quality of life.
Why it matters
Potential benefit: If successful, this work could lead to more accurate predictions about advanced cancer progression, allowing patients to receive timely advance care planning and palliative care tailored to their needs.
How similar studies have gone: While machine learning algorithms for mortality risk have been validated, this project explores a novel approach to integrate these tools with clinician decision-making.
Where this research is happening
-
Emory University
Atlanta, United States Active
Researchers
- Principal investigator: Parikh, Ravi Bharat — Emory University
- Study coordinator: Parikh, Ravi Bharat
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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.