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Product:
Genki
Version 2
Company HQ:
Delaware, USA
Download Product Profile
Last Updated:
29 September 2021
Genki highlights regions of a chest X-ray that have specific abnormalities associated with tuberculosis (TB) and helps radiologists to prioritize and reduce their workload. Genki can be an adaptive system that, if deployed online, evolves over time based on every new X-ray read in the field. Along with displaying the heat map, outline and bounding boxes, it also automatically generates a radiology report compliant with Radiological Society of North America standards. A human-verified signed report from a board certified radiologist can also be made available if required.
Demo site available on request. Please email info@deeptek.ai.
Certification
CE (pending), FDA (pending)
Development Stage
On the market
Deployment
Online & offline
Intended Age Group
14+ years
Target Setting
Primary health centres, general hospitals, teleradiology
centres, large-scale government-run TB screening programmes, etc.
Current Market
India, Asia-Pacific region and Africa.
Future market (after CE/FDA certification): USA, Europe and Japan.
Input
High quality posterior-anterior or anterior-posterior chest X-ray image in DICOM/PNG/JPG formats
Output
Structured report including:
»» Heat map showing regions suspected of TB
»» Probability score for TB
»» Probability scores for 20+ pulmonary abnormalities other than TB
1/1
Hardware
i5 processor or equivalent, 8 GB RAM, 1 TB hard-drive (for local installation)
Validation
The product has been internally and externally validated by several researchers, customers, and healthcare foundations.
Hardware
i5 processor or equivalent, 8 GB RAM, 1 TB hard-drive (for local installation)
Server
Both cloud deployment and local on-premise deployment are supported.
Integration
Integration with existing picture archiving and communication system (PACS) supported.
Software
Cloud deployment: Browser (Chrome, Firefox)
Local deployment: Microsoft Windows / Linux / Docker (all other dependencies will be handled by Docker)
Processing Time
Less than 30 seconds
Data Sharing & Privacy
»» Server location: both cloud deployment and local on-premise deployment are supported.
»» Patient scans are uploaded to the cloud after anonymization and not used for training without patient consent.
»» Data are anonymized before processing.
Software Updates
»» Minor updates monthly (for online only), major updates yearly (for online and offline)
»» Software upgrades are included in the license price
Product Development Method
Supervised and unsupervised deep learning model architectures
Training
The artificial intelligence models were trained on 1.5 million chest X-rays from over 10 countries.
Reference Standard
High-quality radiologist-adjudicated ground truth
Publications
Please visit https://www.deeptek.ai/publications
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