African Coaching Science (Social/Education) | 09 January 2000
AI-Powered Tools in Urban Lagos: Acceptance and Effectiveness for Cystic Fibrosis Early Detection
O, l, u, f, e, m, i, A, i, y, e, t, o, k, e, ,, F, u, n, m, i, l, a, y, o, A, d, e, k, u, n, b, i
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