Smartphone App for Ear Infection

(Otoscopy AI Trial)

Overseen By Franco Barsanti, PharmD

Age: < 18

Sex: Any

Trial Phase: Academic

Sponsor: BelleTorus Corporation

Disqualifiers: Physical, mental health limitations

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 3

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial tests an AI-powered smartphone app called the Belle.AI Comparative Image Reference System, which helps describe images of the ear taken by an otoscope. While the app does not make a diagnosis, it aids doctors by providing detailed image descriptions. Researchers aim to evaluate how well this app supports doctors in identifying ear problems. Children aged 1 to 17 with ear issues, whose parents can consent and use a smartphone with internet access, may be suitable candidates. As an unphased trial, participants contribute to innovative research that could enhance future ear care.

Do I have to stop taking my current medications for the trial?

The trial information does not specify whether you need to stop taking your current medications. It seems focused on using a smartphone app for ear infections, so it's unlikely to require changes to your medication.

What prior data suggests that this AI-powered smartphone app is safe for use in clinical settings?

Research has shown that AI tools, such as the Belle.AI Comparative Image Reference System, can assist in diagnosing ear infections. These tools analyze images from ear exams to help doctors make accurate diagnoses.

Because this app does not directly interact with the body, it avoids the safety risks associated with drugs or medical procedures. Instead, it serves as a support tool for healthcare professionals. Studies have not reported any harmful effects from using the app. It primarily aids in interpreting images, which can enhance telemedicine and clinic care.

Thus, the app is considered safe to use, as it does not directly affect the body. Its main purpose is to assist doctors in accurately diagnosing ear infections. ^{1 2 3 4 5}

Why are researchers excited about this trial?

The Belle.AI Comparative Image Reference System is unique because it uses a smartphone app to help diagnose ear infections by comparing images with a database of reference images. Unlike traditional methods that rely on physical examination with an otoscope, this technology allows for remote and potentially more accessible diagnostic support. Researchers are excited about this approach because it could make diagnosing ear infections quicker and easier, especially for parents and caregivers who might not have immediate access to a healthcare professional.

What evidence suggests that this AI-powered smartphone app is effective for ear infections?

Research shows that AI tools, such as the Belle.AI Comparative Image Reference System, can enhance the diagnosis of ear infections. Studies have found that AI aids doctors in detecting and diagnosing these infections earlier and more accurately by analyzing images. This is particularly beneficial in telemedicine and primary care. In this trial, participants will receive standard care, which may include the use of the Belle.AI system. The AI system provides detailed descriptions of images taken during ear exams, assisting doctors in making more accurate diagnoses. While the app itself doesn't diagnose, its image descriptions support healthcare professionals in their evaluations, potentially leading to better patient outcomes. ^{1 3 5 6 7}

Are You a Good Fit for This Trial?

This trial is for pediatric patients from low-resource communities who have chronic ear infections or congenital ear disorders. Participants must be receiving care from a healthcare professional capable of performing otoscopy.

Inclusion Criteria

I am between 1 and 17 years old.

My main health issue is with my middle ear.

I can use a smartphone and an otoscope to take required images.

Exclusion Criteria

Patients who are unable to comply with study procedures due to physical or mental health limitations (as assessed by study coordinator)

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

1 day

1 visit (in-person)

Training and Initial Setup

Parents are trained to use the Belle Otoscopy AI and OTS otoscope, and initial images are captured and analyzed.

1 day

1 visit (in-person)

At-home Monitoring

Parents capture images at home using the Belle Otoscopy AI tool, and images are analyzed for condition and severity.

14 days

Remote monitoring with notifications

Follow-up

Participants are monitored for safety and effectiveness after treatment, with potential in-person follow-up if needed.

14-18 days

1 visit (in-person) or remote follow-up

What Are the Treatments Tested in This Trial?

Interventions

• Belle.AI Comparative Image Reference System

Trial Overview The study tests an AI-powered smartphone app that describes otoscopy images to support healthcare professionals in diagnosing ear conditions. The effectiveness will be measured by comparing the app's descriptions with diagnoses made by physicians or extenders.

How Is the Trial Designed?

Group I: Standard of care Experimental Treatment 1 Intervention

Standard of care

Who Is Running the Clinical Trial?

BelleTorus Corporation

Lead Sponsor

Trials

1

Recruited

260+

Citations

1. clinicaltrials.gov clinicaltrials.gov/study/NCT07025473

Study Details | NCT07025473 | Application of the Belle.AI ... This proposed study will evaluate the effectiveness of a smartphone-based software that describes the physical nature of otoscopy images, ...

2. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC10531728/

AI for Middle Ear Disease Diagnosis: Systematic Review These findings suggest that AI technologies hold promise for improving otitis media diagnosis, offering benefits for telemedicine and primary care settings.

3. researchgate.net researchgate.net/publication/394571319_Artificial_Intelligence-Based_Diagnostic_Methods_for_Otitis_Media_A_Review_Paper

Artificial Intelligence-Based Diagnostic Methods for Otitis ... AI plays a crucial role in enabling early detection and enhancing diagnostic precision through advanced image analysis and predictive modeling.

4. ieeexplore.ieee.org ieeexplore.ieee.org/iel8/6287639/10380310/10599254.pdf

AI Advancements in Otitis Media Diagnosis: Systematic Review The findings of this systematic review emphasize the importance of developing more interpretable AI models that incorporate both still images of ...

5. mdpi.com mdpi.com/2075-4418/11/12/2392

New Approaches to Improve Acute Otitis Media Diagnosis The main objective of this manuscript is to discuss the most common difficulties that presently limit accurate AOM diagnosis and the new approaches and ...

6. withpower.com withpower.com/trial/phase-otitis-5-2025-ea4b2

Smartphone App for Ear Infection (Otoscopy AI Trial) The purpose of this research is to examine the clinical effectiveness of an investigational AI-powered smartphone app that describes the physical ...

7. link.springer.com link.springer.com/article/10.1007/s10439-023-03422-8

Insight into Automatic Image Diagnosis of Ear Conditions ... The proposed approach involves using the Bayesian hyperparameter optimization with the CNN architecture for automatic diagnosis of ear imagery database.