MediAI-BA

Crescom

MediAI-BA is a web-based AI solution for automatic analysis of bone age, skeletal maturity indicator, and adult height prediction, featuring a patented hybrid analysis algorithm based on both GP and TW3 combined.

Information source: Vendor
Last updated: July 9, 2024

General Information

General
Product name	MediAI-BA
Company	Crescom
Subspeciality	MSK
Modality	X-ray
Disease targeted	Growth disorder, short or tall stature, early or late puberty, orthodontics, child obesity
Key-features	Bone age based on GP and TW3 hybrid, bone age of key ROI, predicted adult height (Middle-Parental Height, AHP, BP), growth status tracking
Suggested use	During: perception aid (prompting all abnormalities/results/heatmaps), interactive decision support (shows abnormalities/results only on demand), report suggestion

Technical Specifications

Data characteristics
Population	Patients under age of 18 regardless of gender or ethnicity
Input	X-ray image of hand bone
Input format	DICOM, png, jpg, jpeg
Output	Automatically generated structured report
Output format	pdf, html
Technology
Integration	Integration in standard reading environment (PACS), Stand-alone webbased
Deployment	Cloud-based
Trigger for analysis	On demand, triggered by a user through e.g. a button click, image upload, etc.
Processing time	3 - 10 seconds

Regulatory

Certification
CE	Certified, Class I , MDD
FDA	No or not yet
Intended Use Statements
Intended use (according to CE)

Market

Market presence
On market since	03-2020
Distribution channels	<5
Countries present (clinical, non-research use)	<10
Paying clinical customers (institutes)	>300
Research/test users (institutes)	<5
Pricing
Pricing model	Subscription
Based on	Number of analyses

Evidence

Evidence
Peer reviewed papers on performance	Prediction of Fishman’s skeletal maturity indicators using artificial intelligence (Scientific Reports, 2023) (read) Clinical Validation of a Deep Learning-Based Hybrid (Greulich-Pyle and Modified Tanner-Whitehouse) Method for Bone Age Assessment (Korean Journal of Radiology, 2021) (read)
Non-peer reviewed papers on performance
Other relevant papers