Nigerian startup Aajoh is beta testing an e-health tool that uses artificial intelligence (AI) to diagnose patients.
Aajoh chief executive officer (CEO) Simi Adejumo was one of nine African entrepreneurs selected to attend the MITx Global Entrepreneurship Bootcamp in Cambridge, Massachusetts in August of last year.
Since then Aajoh has been in development, but it is now in private beta testing in Lagos with plans to expand from there.
The startup’s solution allows individuals to input health symptoms via text, audio and photographs to obtain a diagnosis instantly using AI.
“A way to think about this is we replicate and improve the physical interaction with a medical doctor and place it on a mobile phone which is accessible to individuals, thus placing healthcare in their palms,” Adejumo told Disrupt Africa.
“Users access this by inputting their health symptoms to get an accurate diagnosis instantly and then purchase prescribed medication. Other features of the platform include live consultation with a medical doctor and the ability to book appointments with hospitals.”
The Aajoh app was developed using patient-generated data, with users’ health symptoms used to generate a model. This process is ongoing in order to improve the performance of the app.
“The aim of this was to use data in its purest form and also this enables us to scale faster than the use of traditional hospital data,” Adejumo said.
Aajoh launched in March of this year, focused on using tech to solve Africa’s healthcare problems.
“Citizens in developing countries have a hard time accessing quality healthcare. When we dug deeper we realised individuals solved this problem by self-medicating from drug stores,” said Adejumo.
The startup has already secured partnerships with two hospitals in Nigeria, with over 32,000 data entries combined. The beta test is being conducted with 34 select users, while there are over 500 people on a waiting list. Adejumo plans to expand elsewhere in Africa by early 2019.
“Our ultimate goal is to move healthcare from the current reactive state to a predictive state where we can predict if and when individuals would fall ill,” he said.
