Darlington Ahiale Akogo: Coding the Future of African Diagnostics

In 2013, a young Ghanaian man named Darlington Ahiale Akogo spent six exhausting hours in an Accra clinic waiting to see an Ear, Nose, and Throat (ENT) specialist for a common infection. In a region where the doctor-to-patient ratio is often one to 8,000, such delays are not just an inconvenience; they are a systemic failure that costs lives. Darlington, who has his roots in Europe, looked at the crowded waiting room and saw "Ground Zero" for a technological revolution. He realised that Africa did not just need more doctors; it needed "digital doctors", automated systems capable of high-precision diagnostic intelligence.

Returning to Ghana against the initial wishes of his family, Darlington founded MinoHealth AI Labs to address the acute shortage of medical specialists. He began in a tiny office in Accra, working alone to develop AI systems that could interpret medical images with the accuracy of a seasoned radiologist. His focus was clear: medical imaging is the bedrock of modern diagnosis, yet many African hospitals have the hardware but lack the specialists to read the results. MinoHealth was designed to close this gap by automating the detection of health conditions, like pneumonia, fibrosis, hernia, and various cancers.

The technical depth of Darlington’s work is formidable. One of his lab’s core innovations is "ScaffoldNet," a Convolutional Neural Network (CNN) designed for the classification of biomedical polymer-based scaffolds; a research paper that has been recognised in global scientific volumes. Unlike narrow AI tools built for Western demographics, MinoHealth systems are trained on localised, robust datasets to ensure diagnostic equity. Through partnerships with the Lacuna Fund and Makerere AI Lab, Darlington is developing datasets specifically for the diagnosis of Malaria using AI, tackling a disease that remains a primary health threat in Africa. Today, MinoHealth’s diagnostic tools are achieving over 95% accuracy in several applications, drastically reducing the time between testing and treatment.

Darlington’s influence has scaled far beyond the lab. He is now a recognised voice in global AI governance, serving as the Chair of the Topic Group on AI for Radiology under the United Nations (ITU) and World Health Organisation (WHO). At the continental level, he leads the working group for the African Union’s AI Economy, helping draft the Continental AI Strategy that will guide 54 member states into the Fourth Industrial Revolution. His philosophy of "sovereign AI" emphasises that Africa must not only consume technology but must build and govern its own digital infrastructure.

Beyond healthcare, Darlington’s ecosystem of innovation includes karaAgro AI, which applies computer vision to agriculture for pest detection and crop yield optimisation, and the Runmila AI Institute, which trains the next generation of African data scientists in deep learning. He believes that AI is the definitive tool to solve the continent’s most persistent problems, from food security to universal health access. Recognised as a Forbes Africa 30 Under 30 honoree and one of the Top 100 Most Influential People of African Descent, Darlington Ahiale Akogo is proving that African makers are no longer waiting for the future; they are coding it.

Lessons for Budding Makers

Darlington Ahiale Akogo's journey offers valuable insights for aspiring creators and entrepreneurs:

1. Solve for "Ground Zero": True innovation often comes from returning to the places with the most significant infrastructure gaps and applying high-tier technology to solve foundational human needs like healthcare access.
2. Build Ecosystems, Not Products: To ensure long-term success, don't just build a single tool; create a supporting ecosystem of education and policy, as seen with Darlington’s work in training and global standard-setting.