Rho AI Software for Osteoporosis

Overseen By Maria Flory

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: University of Wisconsin, Madison

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

Compensation: Varies

Number of Visits: Unknown

800 Participants Needed

Trial Summary

Do I need to stop my current medications for this trial?

The trial information does not specify whether you need to stop taking your current medications.

What data supports the effectiveness of the Rho AI Software treatment for osteoporosis?

Research shows that using machine learning models, like those in Rho AI Software, can predict bone mineral density response and personalize treatment plans for osteoporosis, leading to a 9.54% improvement in treatment response compared to standard regimens. ^{1 2 3 4 5}

How does the Rho AI Software treatment for osteoporosis differ from other treatments?

Rho AI Software for osteoporosis is unique because it uses artificial intelligence to help manage the condition by predicting risk factors, classifying patients, and recommending personalized exercise programs. This approach is different from traditional treatments that primarily focus on medication and does not typically involve AI-driven personalized care. ^{2 3 6 7 8}

What is the purpose of this trial?

To assess the effectiveness of 16bit's Rho AI (artificial intelligence) software at identifying known cases of osteoporosis. 800 de-identified images from January 2007 to January 2024 will be accessed to test the software prospectively.

Research Team

James Bernatz, MD

Principal Investigator

UW School of Medicine and Public Health

Eligibility Criteria

This trial is for individuals with de-identified images from January 2007 to January 2024 that can be used to test the Rho AI software's ability to detect osteoporosis. Specific eligibility criteria are not provided.

Inclusion Criteria

Images from people who have undergone spine fusion

Images from people who have undergone total joint arthroplasty

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Data Collection

De-identified x-ray images are collected and processed through the Rho AI software to identify osteoporosis or osteopenia

1 month

Follow-up

Participants are monitored for safety and effectiveness after data collection

4 weeks

Treatment Details

Interventions

• Rho AI Software

Trial Overview The study aims to validate the effectiveness of Rho AI software in identifying cases of osteoporosis using a set of 800 de-identified images collected over a period spanning from January 2007 to January 2024.

Participant Groups

Group I: Experimental Detection of Osteoporosis Experimental Treatment 1 Intervention

Who Is Running the Clinical Trial?

University of Wisconsin, Madison

Lead Sponsor

Trials

1,249

Recruited

3,255,000+

References

1. England pubmed.ncbi.nlm.nih.gov

Bone mineral density response prediction following osteoporosis treatment using machine learning to aid personalized therapy. [2021]

2. England pubmed.ncbi.nlm.nih.gov

Artificial intelligence used to diagnose osteoporosis from risk factors in clinical data and proposing sports protocols. [2022]

3. United States pubmed.ncbi.nlm.nih.gov

Machine Learning Solutions for Osteoporosis-A Review. [2021]

4. United States pubmed.ncbi.nlm.nih.gov

New Horizons: Artificial Intelligence Tools for Managing Osteoporosis. [2023]

5. Switzerland pubmed.ncbi.nlm.nih.gov

Development of Machine Learning Models for Prediction of Osteoporosis from Clinical Health Examination Data. [2021]

6. Switzerland pubmed.ncbi.nlm.nih.gov

[Does artificial intelligence have a role in osteoporosis management?] [2023]

7. Korea (South) pubmed.ncbi.nlm.nih.gov

Prediction of medication-related osteonecrosis of the jaw (MRONJ) using automated machine learning in patients with osteoporosis associated with dental extraction and implantation: a retrospective study. [2023]

8. England pubmed.ncbi.nlm.nih.gov

Artificial intelligence on the identification of risk groups for osteoporosis, a general review. [2023]