Noninvasive diagnosis of middle-ear problems using advanced data analysis
Official title: Objective and noninvasive diagnosis of middle-ear and conductive pathologies using simulation-based inference and transfer learning applied to clinical data
Funded at California State University Sacramento · NIH-10839978 · Data updated 2026-11-12
This study is working on a new, easy way to diagnose ear problems that cause hearing loss, using advanced technology to analyze ear measurements without any painful procedures, so that more people can get the help they need quickly and safely.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | California State University Sacramento NIH-funded |
| Lab location | 1 site (Sacramento, United States) |
| Project start | May 1, 2022 |
| Project end | April 30, 2026 |
| Funding year | 2024 |
| Award (this year) | $177,500 |
| NIH project number | 5R21DC020274-04 |
| Project ID | NIH-10839978 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals of all ages experiencing symptoms of conductive hearing loss.
✕Less likely to help
Patients with sensorineural hearing loss or those who do not exhibit symptoms of middle-ear pathologies may not benefit from this research.
What this research studies
This research aims to develop a new method for diagnosing middle-ear pathologies that cause conductive hearing loss, which affects many individuals. By utilizing wideband tympanometry (WBT) and machine learning techniques, the study seeks to analyze complex data from ear measurements to identify specific conditions without the need for invasive procedures. This approach could help reduce the reliance on costly imaging and exploratory surgeries, making diagnosis safer and more accessible for patients. The goal is to create a reliable, noninvasive diagnostic tool that can improve patient outcomes and streamline treatment decisions.
Why it matters
Potential benefit: If successful, this research could lead to more accurate and safer diagnoses of middle-ear conditions, ultimately improving treatment options for patients with conductive hearing loss.
How similar studies have gone: While machine learning applications in medical diagnostics are emerging, this specific approach to middle-ear assessment is relatively novel and has not been extensively tested.
Where this research is happening
-
California State University Sacramento
Sacramento, United States Active
Researchers
- Principal investigator: Motallebzadeh, Hamid — California State University Sacramento
- Study coordinator: Motallebzadeh, Hamid
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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.