JLD-01K

JLK Inc.

JLD-01K is based on the Convolutional Neural Network (CNN), a type of deep learning model, that detects nodules in pulmonary CT images. Measure the diameter and volume of the nodules found, proceed quantitatively, categorize the LungRADs category, and specify the total number of nodules per patient. In addition, 2D views of Axial, Coronal, Sagittal, etc. are provided through the web-based UI, and lungs and nodules are visualized and displayed through 3D views.

Information source: Vendor
Last updated: July 1, 2020

General Information

General
Product name	JLD-01K
Company	JLK Inc.
Subspeciality	Chest
Modality	CT
Disease targeted	Lung cancer
Key-features	Lung nodules detection and quantification, LungRADs categorization, Vancouver Risk calculator, report generation
Suggested use	During: perception aid (prompting all abnormalities/results/heatmaps), report suggestion

Technical Specifications

Data characteristics
Population	All chest CT
Input	Lung CT
Input format	DICOM, JPG
Output	Location annontation, nodule diameter and volume, LungRADs category, Vancouver Risk Calculator
Output format	UI, Report
Technology
Integration	Stand-alone third party application
Deployment	Locally on dedicated hardware, Cloud-based, Hybrid solution
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	09-2019
Distribution channels
Countries present (clinical, non-research use)	3
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing
Pricing model	Pay-per-use, Subscription
Based on	Number of users, Number of installations

Evidence

Evidence
Peer reviewed papers on performance
Non-peer reviewed papers on performance
Other relevant papers