Improving predictions of disease cure using machine learning
Using Machine Learning to Improve the Predictive Accuracy of Disease Cure
['FUNDING_R15'] · UNIVERSITY OF TEXAS ARLINGTON · NIH-10654253
This study is working on a smart tool that uses computer technology to help doctors figure out which patients with early-stage diseases might get better on their own, so they can avoid harsh treatments, while also identifying those who need quick care to stay healthy.
Quick facts
| Phase | ['FUNDING_R15'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | UNIVERSITY OF TEXAS ARLINGTON (nih funded) |
| Locations | 1 site (ARLINGTON, UNITED STATES) |
| Trial ID | NIH-10654253 on ClinicalTrials.gov |
What this research studies
This research aims to develop a predictive model that utilizes machine learning techniques to accurately identify patients who are likely to be cured of early-stage diseases. By analyzing pre-treatment characteristics and survival data, the model will help distinguish between patients who can safely avoid aggressive treatments and those who need timely intervention to prevent disease progression. The approach addresses limitations of existing predictive models, enhancing their robustness and applicability in clinical settings.
Who could benefit from this research
Good fit: Ideal candidates for this research are patients diagnosed with early-stage diseases who are undergoing treatment and have available pre-treatment data.
Not a fit: Patients with advanced-stage diseases or those who do not have sufficient pre-treatment data may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more personalized treatment plans, reducing unnecessary treatments for cured patients and improving outcomes for those who are not yet cured.
How similar studies have performed: Previous research has shown promise in using machine learning for predictive modeling in healthcare, indicating potential success for this novel approach.
Where this research is happening
ARLINGTON, UNITED STATES
- UNIVERSITY OF TEXAS ARLINGTON — ARLINGTON, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: PAL, SUVRA — UNIVERSITY OF TEXAS ARLINGTON
- Study coordinator: PAL, SUVRA
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 below.
Conditions: Disease, Disorder, Infection