Dr Ayomide Oladosu, a Senior Research Associate at the School of Transdisciplinary Studies of The Hang Seng University of Hong Kong (HSUHK), presents novel research on leveraging artificial intelligence (AI) to address mental health challenges in low-resource settings at the Hong Kong International Mental Health Conference.

The presentation, titled “Leveraging Artificial Intelligence in the Prediction, Diagnosis, and Treatment of Depression and Anxiety Among Perinatal Women in Low- and Middle-Income Countries (LMICs),” highlighted the critical gap in mental healthcare for pregnant women during and after pregnancy in underserved regions.

During the presentation, Dr Oladosu engaged with international scholars, clinicians, and policymakers, discussing the potential of AI models to revolutionize maternal mental healthcare. The research proposes using machine learning algorithms to analyze data from mobile phones and low-cost devices (such as speech patterns, social engagement, and sleep data) to create early-warning systems for depression and anxiety. “This isn’t about replacing clinicians, but about empowering communities and stretching scarce resources,” explained Dr Oladosu. “In many LMICs, there can be as few as one mental health professional for every 100,000 people. Our research explores how AI can serve as a force multiplier, helping community health workers identify at-risk women much earlier and connect them to the limited support available.”

The proposed AI-driven framework aims to achieve three key objectives:

1. Prediction: Identify women at high risk of developing perinatal mental health issues based on demographic, behavioral, and social determinants.
2. Diagnosis: Assist in screening and diagnosis through analysis of simple, non-invasive data inputs, making the process more accessible and less stigmatizing.
3. Treatment: Personalize and recommend evidence-based interventions, from digital cognitive behavioral therapy (CBT) modules to prompts for peer support, all deliverable via basic smartphones.

The presentation sparked lively discussions on the ethical implementation of such technology, including data privacy, algorithmic bias, and the importance of cultural adaptation. Delegates from various institutions expressed strong interest in the potential for cross-border collaborations to pilot and validate these AI tools.

“This work sits at a crucial intersection of global public health, technology, and social policy,” Dr Oladosu added. “The positive feedback and insightful questions from conference delegates have been invaluable in shaping the next phase of our research, which will focus on pilot studies in specific LMIC contexts.” The Hong Kong International Mental Health Conference serves as a key platform for sharing the latest scientific advancements and fostering dialogue among leading experts in the field. Dr Oladosu’s research contributes to HSUHK’s growing reputation for innovative, impact-driven research that addresses pressing global challenges.