How AI Is Transforming Cancer Detection

A Conversation with Doyin Badamosi

Cancer doesn't live in statistics. It lives in our homes and families. In Ireland, where one in two people will face a cancer diagnosis in their lifetime, this disease leaves few families untouched. The good news is that artificial intelligence is quietly revolutionising how we detect and treat disease.

Physicist and AI innovator Doyin Badamosi is at the forefront of this transformation. Through his companies Durotimi AI Technologies and Radmol AI Systems, he is embedding cancer screening algorithms into routine GP visits and tackling radiology errors that delay critical diagnoses.

Early Detection Before Symptoms Arise

Durotimi AI Technologies embeds cancer screening algorithms directly into routine GP visits. The system analyses patient history, genomic data, and test results in real time to flag cancer risk before symptoms present. This proactive approach shifts healthcare from reactive treatment to preventative care.

The technology integrates seamlessly into existing GP workflows across Ireland and the UK. Rather than replacing physicians, it augments their decision-making capabilities with data-driven insights.

Addressing Radiology's Hidden Crisis

Radmol AI Systems tackles one of oncology's most pressing challenges: radiology reporting errors. Studies indicate that up to 30% of radiology cases contain errors that can delay critical diagnoses. Badamosi's AI models are trained to highlight anomalies and support radiologists rather than replace them.

The system acts as a safety net, catching potential oversights and ensuring patients receive timely interventions. This human-AI collaboration represents the future of diagnostic medicine.

Building Ethnically Diverse AI Models

A critical insight from Badamosi's work is the importance of localised AI models. Many existing healthcare AI systems are trained predominantly on Western datasets, leading to bias and reduced accuracy for other populations.

Badamosi's team, active since 2023, is partnering with Mayo Clinic (using 3 million patient records) and two African governments to build ethnically diverse, localised AI models. This approach ensures the technology works effectively across different countries and ethnicities.

Global Impact: The Urgency in the Global South

Early detection AI is most urgently needed in the Global South, where just 3 in 10 children with cancer survive—compared to 8 in 10 in the West. This disparity stems largely from delayed diagnosis and GP shortages.

By embedding AI screening into routine healthcare visits, Badamosi's technology can help bridge this gap, bringing world-class diagnostic capabilities to underserved regions.

Conclusion

AI in healthcare is not about replacing human expertise—it is about amplifying it. Doyin Badamosi's work demonstrates how machine learning can detect cancer earlier, reduce diagnostic errors, and ultimately save lives. For organisations across Ireland and the UK exploring AI adoption, his approach offers a blueprint for responsible, impactful implementation.

Want the full conversation? Watch the Chatting GPT episode on YouTube here: https://www.youtube.com/watch?v=5fWQVyVdldc