Improving diagnosis for rare diseases using advanced data analysis
Learning Precision Medicine for Rare Diseases Empowered by Knowledge-driven Data Mining
['FUNDING_R01'] · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · NIH-10922807
This study is working to make it easier for doctors to diagnose rare diseases faster by creating a helpful online resource that gathers the latest information about these conditions, especially those caused by new gene mutations, so patients can get the answers they need more quickly.
Quick facts
| Phase | ['FUNDING_R01'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON (nih funded) |
| Locations | 1 site (HOUSTON, UNITED STATES) |
| Trial ID | NIH-10922807 on ClinicalTrials.gov |
What this research studies
This research aims to enhance the diagnosis of rare diseases by developing a comprehensive knowledge hub that consolidates the latest information and findings related to these conditions. By leveraging advanced data mining techniques, the project seeks to address the significant delays patients face in receiving accurate diagnoses, which can average six years. The collaboration between the Mayo Clinic and Vanderbilt University Medical Center will facilitate the creation of an informatics framework that helps clinicians access and utilize critical information efficiently. This initiative focuses on rare diseases, particularly those with novel gene mutations that are often overlooked in existing databases.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals suffering from rare diseases who have experienced long diagnostic delays.
Not a fit: Patients with common diseases or those who have already received a timely diagnosis may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could significantly reduce the time it takes for patients with rare diseases to receive accurate diagnoses and appropriate treatments.
How similar studies have performed: Other research initiatives have shown promise in utilizing data mining for improving diagnosis in rare diseases, indicating a potential for success in this novel approach.
Where this research is happening
HOUSTON, UNITED STATES
- UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON — HOUSTON, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: LIU, HONGFANG — UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
- Study coordinator: LIU, HONGFANG
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: Cardiac Diseases, Cardiac Disorders, Cardiovascular Diseases, Chronic Obstruction Pulmonary Disease, Chronic Obstructive Lung Disease