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Product:

1.0.0.0

JLD-02K (JVIEWER-X)

Company HQ: 

Seoul, Republic of Korea

Last Updated:

August 31st, 2020

JVIEWER-X has dual-purpose: firstly, it can be used as triage and prioritization tool for radiologists or teleradiologists. Secondly it can be used to as an automated chest X-ray interpretation tool that can detect several pulmonary abnormalities, including signs of tuberculosis and others : atelectasis, consolidation, fibrosis, mass, nodule, pleural effusion, pneumothorax, pneumonia, cardiomegaly, effusion, infiltration, edema, emphysema, fibrosis, hernia and COVID-19.

Certification

CE-marked, Korea FDA, Australia FDA

Development Stage

On the market

Deployment

Online & offline

Intended Age Group

10+ years (regulatory approval)

Target Setting

Primary health centers, general hospital (above primary level), teleradiology companies, government/public sector, e.g. national TB program, private sector

Current Market

South Korea, USA, India, China, Japan, Indonesia, Laos, Thailand, Russia, Dubai, and Brazil

Input

»» Can be used to read images from any kind of chest Xray machine

»» X-ray image format: JPEG, PNG, DICOM

»» Chest X-ray type: posterior-anterior chest X-ray, anterior-posterior chest X-ray, portable

»» Other requirements: Only X-ray image

Output

A structured report consists of:

»» Probability score for each abnormailty as well as dichotomous output indicating whether the abnormality is present or absent,

»» Probabilty score for TB as well as dichotomous output indicating whether TB is likely present or likely absent,

»» Heat map.  

Default threshold probability score: 50% but can be adjusted.

The product can detect the lung abnormalities: tuberculosis, atelectasis, consolidation, fibrosis, mass, nodule, pleural effusion, pneumothorax, pneumonia, cardiomegaly, effusion, infiltration, edema, emphysema, fibrosis, hernia and COVID-19. 

Server

Minimum 16 GB RAM, Ubuntu 16.04

Integration

It is possible to integrate the product with the client’s legacy picture archiving and communication system (PACS). Please contact the sales team at khpaik@jlkgroup.com.

Software

Windows 10, minimum 8 GB RAM

Processing Time

15-20 seconds (depending on the performance of the hardware)

Hardware

Product does not need GPU (offline solution case). Intel 5 or higher generation CPU with Intel Graphics, Full HD monitor, Recommended 20GB HDD or SDD. Compatible with laptop or miniPC.

Validation

Validation only required if chest X-ray images are from a low dose machine that affects the image quality.

Data Sharing & Privacy

»» Server Location: the product can be set up in a public cloud such as Azure or AWS

»» Data is automatically shared with the developer for the online solution but not for the offline solution. In the online solution (via cloud), the developer cannot access the X-ray database, and the data is automatically deleted after 24 hours.

»» There is an option to de-identify data. The X-ray data is anonymized before AI analysis.

Software Updates

»» Software is updated twice a year

»» Please contact the company's sales team at khpaik@jlkgroup.com for pricing information

Price

»» Please contact the company's sales team at khpaik@jlkgroup.com for pricing information

»» There is a pricing difference between online and offline solutions.

»» Please contact company's sales team at khpaik@jlkgroup.com for details on upfront installation and set up costs

Product Development Method

Supervised deep learning (CNN, DBNs)

Training

The product was trained on 1 500 000 chest X-rays from South Korea, Malaysia, India, Indonesia, China and South Africa

Reference Standard

Culture, smear, GeneXpert, CT and human reader

Publications

»» Peer-reviewed publications are not yet available.

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