A machine learning malarial retinopathy diagnostic tool, consisting of a 3D printed camera attachment and a mobile-powered application.
Cipher is a malarial retinopathy diagnostic tool with manufacturing headquarters in Lagos, Nigeria. The product is designed and manufactured by MicroFuse Technologies and aims to diagnose the disease with at least 90% accuracy.
The target region for this product is Sub-Saharan Africa.
The manufacturer distributes the product.
SDG 3: Good health and well-being
Hospitals and health clinics, as well as ministries of health in remote regions.
The hardware component for this product is manufactured in Lagos, Nigeria. The accompanying application is deployed and available for most smartphone operating systems.
Users can obtain the product directly from the manufacturer.
As of 2020, there are 20 implementations of this product with a further 700 potential customers.
Connectivity requirement for the product/service to work (mobile internet, SMS, voice, fixed internet, Wi-Fi, other [specify]).
Coverage required for the product/service to work (2G, 3G, 4G, LTE, broadband, dial-up, other [specify]).
Device features required for the product/service to work (bluetooth, Wi-Fi, camera, IVR, GPS, accelerometers/motion sensors, physiologic biosensors, biometric identifiers, SIM, memory card (e.g microSD), other [specify]).
Device(s) type required for the product/service to work (smartphone, feature phone, computer, tablet, other [specify]).
Connectivity requirement for the product/service to work. Some apps/services can work offline. If no, specify if network connectivity is needed at any point (e.g connectivity needed for download).
Is the product/service able to receive and send back information to the user?
Rates of user vs downloads/subscriptions – Compliance rate for the eHealth service
Support according to the literacy level required from the user. If yes, specify type of literacy support. If no, the user is intended to be literate.
Operating system required and software version (Android, IOs, Windows, other [specify])
Power supply required for the product/service to work (uninterrupted prower supply (UPS), ocassional power supply [minimum time required], other).
Education and behavior change, human resource management, decision support, data collection & analytics, electronic medical records, Healthcare provider- CHW training, telemedicine/remote diagnostic, stock management, disease surveillance and reporting
Cipher is a mobile application with data input through images captured through smartphone camera devices with a provided camera attachment. The images are processed through the artificial intelligence system built using the DarkNet YOLO Machine Learning Algorithm for Deep Learning, to determine the diagnosis of malarial retinopathy. The mobile application provides diagnosis and recommended next steps for the patient.
Technical support is provided in the user manual, with further support available by contacting the manufacturer.
Replacement components for the camera attachment are available from the manufacturer.
The manufacturer quotes the following performance targets: level of accuracy (<90%), efficiency, speed of diagnosis, ease of use, non-invasive.
As of 2020, the product is undergoing clinical trials at 4 University Teaching Hospitals in Nigeria.
No known safety hazards related to this product.
The mobile application provides diagnosis as well as the next steps following results.
Standards ISO13485:1996, ISO13488:1996, ISO 14971
The product is evaluated for 90% accuracy for diagnosis as an evaluation. The manufacturer also cites non-invasive and speed, of diagnosis as evaluation criteria.
Cipher was a product entered in the ASME iSHOW Kenya 2020.
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