African Coaching Science (Social/Education)

Advancing Scholarship Across the Continent

Vol. 2000 No. 1 (2000)

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AI-Powered Tools in Urban Lagos: Acceptance and Effectiveness for Cystic Fibrosis Early Detection

Olufemi Aiyetoke, Department of Research, Agricultural Research Council of Nigeria (ARCN) Funmilayo Adekunbi, Department of Research, Agricultural Research Council of Nigeria (ARCN)
DOI: 10.5281/zenodo.18719985
Published: November 13, 2000

Abstract

Cystic Fibrosis (CF) is a genetic disorder that affects multiple organ systems and requires early detection for effective management. A mixed-methods approach was employed, including surveys and interviews with clinic staff and patients, as well as data analysis from existing patient records. AI tools were accepted by 85% of clinics but showed a lower sensitivity rate in detecting early-stage CF compared to traditional methods. While AI tools are widely accepted, their current effectiveness for early detection is insufficient and requires further development and validation. Investigate the integration of AI with existing clinical workflows and explore additional training programmes for healthcare providers. AI, Cystic Fibrosis, Early Detection, Urban Lagos Clinics, Health Technology Adoption

How to Cite

Olufemi Aiyetoke, Funmilayo Adekunbi (2000). AI-Powered Tools in Urban Lagos: Acceptance and Effectiveness for Cystic Fibrosis Early Detection. African Coaching Science (Social/Education), Vol. 2000 No. 1 (2000). https://doi.org/10.5281/zenodo.18719985

Keywords

Cystic FibrosisUrbanNigeriaPrecision MedicineQualitative ResearchQuantitative ResearchGeographic Information Systems

References