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

NIH RePORTER · NIH · R44 · $1,499,051 · view on reporter.nih.gov ↗

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
REMMIE, INC.
Principal Investigator
Jane Zhang
Activity code
R44
Funding institute
NIH
Fiscal year
2024
Award amount
$1,499,051
Award type
2
Project period
2022-12-01 → 2026-05-31