DOI: https://doi.org/10.36347/sjams.2025.v13i09.003

Pages: 1649-1653

The field of ophthalmology has witnessed a considerable expansion in the use of artificial intelligence or AI over the years that passed. Especially, deep learning algorithms are exhibiting particular promise with respect to examining complex data, especially medical images. Around the world, many AI tools have been developed for the diagnosis of ocular disease. However, there is limited evidence on the awareness and readiness of ophthalmology practitioners in a low-resource setting like Sudan toward the adoption of AI for clinical practice. This study was designed to assess the knowledge, attitudes and accessibility of AI technologies among the ophthalmologists and optometrists in Sudan, especially to find the technically acceptable barriers and capacity building areas. In a study with stratified sampling, a cross-sectional survey was undertaken between June and October 2024. There were residents, specialists, consultants, and optometrists working in hospitals and private clinics. Data was collected on demographics, AI knowledge, training, access to AI tools, and perceived clinical impact. Outcomes: A total of 142 practitioners participated, most of whom are aged 30-39 years (57%) and female (77.5%). 40.1% said they were somewhat familiar with AI while just 2.8% said experts. Most of the respondents (19.7%) went for formal AI training offered by international institutes. More than 80% of respondents do not have access to any AI tools. Among those who do have access, applications involving optical coherence tomography (OCT) were most common. Usage patterns differed, with 37.3% never using AI and 23.2% often using it in practice. Almost half (49.3%) feel that AI remarkably enhances workflow, with a third (33.1%) saying it moderately does so. In conclusion, ophthalmology practitioner of Sudan has a major gap in AI awareness, training, and accessibility. To ensure efficient delivery of eye care in low-resource settings, targeted educational initiatives, infrastructure