# Remmie.ai a deep learning diagnostic engine for ear-nose throat disease

> **NIH NIH R44** · REMMIE, INC. · 2024 · $1,499,051

## Abstract

PROJECT SUMMARY
Otitis Media (OM), commonly referred to as an ear infection, is the most common reason for antibiotics use in
children under 6 years of age. OM is also the second-most common cause of hearing loss globally, impacting
1.4 billion individuals in 2017 and currently ranked as the fifth highest disease burden. Otitis media with
effusion (OME) is a condition characterized by the presence of fluid behind the eardrum, often causing hearing
difficulties, while acute otitis media (AOM) refers to a sudden and painful infection of the middle ear, commonly
associated with fever and earache. Perforated eardrum and tympanosclerosis can result from untreated OM,
and these conditions can lead to hearing loss and other complications when left untreated. To prevent
unnecessary and harmful delays to OM diagnosis and management, there is a significant need for widespread,
affordable, and convenient access to otolaryngology specialists. OM is an ideal candidate for real-time
telemedicine visits due to its defined symptoms and visual diagnosis that can be accomplished with
straightforward data points and imaging. However, no platform currently exists to facilitate effective virtual visits
for ear infections. The overall goal of this Phase II project is to further develop and validate Remmie.ai, a next-
generation ear-nose-throat (ENT) mobile health platform, as an innovative telemedicine solution for accurate
and efficient diagnosis of OM. The three aims outlined in this proposal converge to empower Remmie.ai as a
transformative force in healthcare. Aim 1 leverages extensive image and data collection efforts to further refine
Remmie.ai models, enabling precise classification of OM. Aim 2 orchestrates real-world clinical testing to
validate Remmie.ai's effectiveness, assessing its impact on diagnoses and patient care in both in-person and
telemedicine settings. Finally, Aim 3 charts a path towards FDA designation by fortifying the platform's
infrastructure for data privacy and security, ensuring regulatory compliance, and refining the user-friendly
Remmie App. Together, these aims harmonize data-driven AI enhancements, clinical validation, and regulatory
groundwork, propelling Remmie.ai towards its overarching goal of democratizing access to otolaryngology
expertise and improving the diagnosis and management of ENT conditions while safeguarding patient privacy
and adhering to regulatory standards.

## Key facts

- **NIH application ID:** 10921632
- **Project number:** 2R44DC020868-02
- **Recipient organization:** REMMIE, INC.
- **Principal Investigator:** Jane Zhang
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,499,051
- **Award type:** 2
- **Project period:** 2022-12-01 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10921632

## Citation

> US National Institutes of Health, RePORTER application 10921632, Remmie.ai a deep learning diagnostic engine for ear-nose throat disease (2R44DC020868-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10921632. Licensed CC0.

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