Marking a new milestone, we are witnessing an invention that can detect depression early — an extraordinary leap given the devastating toll the condition has long taken.
Professor Nchebe-Jah Iloanusi, a U.S.-based Nigerian scholar, alongside his team has developed an AI model that can pick up the earliest signs of depression– that usually go unnoticed(1). Mental health diagnosis has long depended on traditional methods like- patient self-reporting or clinical observation, which often miss the critical early stages of crisis development(2). This AI model By identifies early markers of depression, like Heart Rate Variability (HRV), Sleep Architecture and Speech Biomarkers, giving doctors and patients a chance to act before the condition escalates into full-blown episodes.
According to the World Health Organization, approximately 332 million people in the world have depression(3). In Africa, with a limitation of resources and infrastructure, this challenge is even more complex. As a result, there has been a focus on strengthening mental health systems (4).
And here we have a model, powered by transformer-based AI architecture, which combines wearable physiological sensors and a unique ability to listen to the nuances of human speech, using large language models (LLMs) to identify patterns that hint at underlying emotional changes. These are woven with biometric data to form a holistic picture of mental health risk-like a finely tuned early warning system(1).
But while the technology is impressive, Professor Iloanusi clarifies that the system is not meant to replace professional mental health care, as no algorithm can replicate the empathy and clinical judgment of a human expert, reminding us that no algorithm can substitute the empathy and judgment of a clinician. Instead, he sees the tool as a supportive one, something that can alert caregivers, empower patients, and prevent crises before they escalate(1).
The possibilities are enormous, yet so are the questions. How do we safeguard sensitive personal data? Can this technology avoid bias across different populations? And will people trust a machine to peer into the hidden corners of their minds? These are the ethical puzzles that must be solved before the model makes its way into everyday use.
Still, one thing is clear: if harnessed responsibly, AI could become a game-changer in psychiatry. By blending science with empathy, it might offer what has long eluded medicine- a chance to intervene before the darkness of depression fully takes hold.
References
1. Ijeoma Nwanosike. Don develops AI model to predict mental health conditions. 2025 Sept; Available from: https://guardian.ng/features/health/don-develops-ai-model-to-predict-mental-health-conditions/
2. AB Newswire. AI Predicts Mental Health Crises Through Social Media With 89% Accuracy, Days Before Clinical Detection, Groundbreaking Review Shows. 2024 Aug; Available from: https://business.wapakdailynews.com/wapakdailynews/article/abnewswire-2025-8-25-ai-predicts-mental-health-crises-through-social-media-with-89-accuracy-days-before-clinical-detection-groundbreaking-review-shows
3. WHO. Depressive disorder (depression). 2025 Aug; Available from: https://www.who.int/news-room/fact-sheets/detail/depression
4. Rebecca Cherop. Strengthening mental health systems in Africa: Introducing the Africa CDC Mental Health Leadership Programme. 2024; Available from: https://scienceforafrica.foundation/media-center/strengthening-mental-health-systems-africa-introducing-africa-cdc-mental-health
