Medsol AI Solutions promotes early breast cancer detection to reduce mortality rates associated with it. They needed our help creating a proof of concept for scanning breast cancer using relevant and accessible technology to scale across Africa.
Languages Kotlin
Tech Sketch, Jetpack, Retrofit, Hilt. Room
Integrations Clarius MobileAPI, Tensorflow
Services In-house Ruby, back-end
What we had to solve
Breast cancer remains one of the highest mortality rates amongst woman in South Africa. This is due to ineffective and delayed diagnosis especially in rural areas. When the Medsol AI Solutions team approached us they had already built their own AI software solution. Medsol AI Solutions’ software uses machine learning to identify and predict breast cancer subtypes. It was our role to design and develop a mobile solution that enabled people across Africa to gain access to this AI Software.
Post Project
France24
Medsol AI Solutions got featured on France24 for launching breast cancer identification software. https://www.france24.com/en/video/20220204-south-african-entrepreneur-launches-software-for-breast-cancer-identification
Saphex 2022 Conference Medsol AI Solutions had a booth at the Saphex 2022 GP Conference where they showed off the software’s reliability, use cases and low cost to reach across Africa.
How we solved the problem
We identified and scoped a technical proof of concept (POC). From there, we implemented the POC to test its viability. Once the POC was proven to be successful, we started with minimum viable product (MVP) for design and development. The app was built using native Android Material guidelines and components.
User Interface and Experience Design
Familiarity Because the Medsol AI Solutions experience needed to be used by many people, it was important to create a familiar and easy-to-use interface. To achieve this we designed the app based on native Android Material guidelines. This reduces the learning curve for people and enables them to get straight to the value of the product.
Hierarchy The most important feature of the app is to access the scanning functionality. We were able to navigate people to this feature with ease by using information architecture and visual hierarchy principles.
Accessibility Different people have different abilities. Creating a solution for everyone means designing a solution that can be used by everyone. We designed the accessibility of the Medsol AI app to include dynamic text, contrast ratios and inclusive imagery.
Android app development
Flexibility We built the Medsol AI Solutions app to scale by developing a modular architecture. This will decreases the cost of new features and time to market.
Usability We used native Android Material components to build accessible features, such as text scaling. We implemented Android App links to provide seamless navigation between MedSol AI Solutions web and mobile.
The final product
The Medsol AI Solutions Android app is fully responsive across mobile and tablet devices, maintaining accessibility and performance. This ensures accurate cancer detection is available to everyone who needs it most.
Medical personnel can use the MedSol AI Solutions app on their phone or tablet to capture patient details, diagnosed ultrasounds scans and note impressions for further referral assessments.
Used with a companion hand-held Clarius scanner, MedSol AI Solutions can accurately provide differential diagnosis in real-time.
Reports are automatically generated with patient information, diagnosed ultrasound images and impressions. These reports can be shared with specialists to help patients receive the correct treatment.
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