GENSCORE
Leveraging Generative AI to Adapt and Enhance Mental Health Assessment in Low-Resource Contexts
Isaac Olufadewa · Slum and Rural Health Initiative · Nigeria
Other team members:
- Ezekiel Oladejo: Co-Investigator (Natural Language Processing [NLP], AI Researcher, Data/Computer Science)
- Ayodele Jegede: Co-Investigator (Ethical Governance, Social Sciences)
- Miracle Adesina: Co-Investigator (Lived Experience Team lead, Community Engagement, Researcher) and ERC Representative
- Olugbenga Owoeye: Co-Investigator (Consultant Psychiatrist, Mental Health Researcher, Clinician)
- Shamsuddeen Muhammad: Co-Investigator (Natural Language Processing [NLP])
- Musa Ayanwale: Co-Investigator (Psychometrician, Digital Health Researcher)
What they're working on
Our GENSCORE Project aims to develop and validate a culturally grounded, multimodal AI platform/software to improve depression and anxiety screening for speakers of Pidgin English, Hausa, and Yoruba in Nigeria. The project will build on our successful pilot to co-develop GENSCORE-DATA v2.0, one of Africa’s largest multilingual mental health datasets, and fine-tune GENSCORE-LLM v2.0 for culturally aligned interpretation. Our culturally relevant model, GENSCORE-LLM, will enable the development of contextually relevant mental health screening (GenPHQ and GenGAD) tools co-designed with people with lived experience and mental health experts. These tools will be integrated into an open-access, multimodal GENSCORE platform that combines voice (audio) and self-reported text, enabling real-time screening and decision support.
AI approach
Multimodal AI · generative AI · multilingual LLMs · voice and text
Mental health focus
Depression · anxiety · screening
Links
Social media
- LinkedIn: https://www.linkedin.com/company/slum-and-rural-health-initiative-network
- X: https://twitter.com/SRHINAfrica
- Instagram: https://www.instagram.com/srhinafrica
- Facebook: https://web.facebook.com/srhinAfrica