Comprehensive Summary
This article provides an overview of how artificial intelligence (AI) can be utilized to improve the design and execution of clinical trials in ophthalmology. While AI is increasingly used in the field, its potential to enhance clinical trials, which are the standard for evidence-based practice, has not been explored much. Many ophthalmic clinical trials do not reach their goals due to insufficient patient enrollment, cost overruns, and sometimes lack reliability. Even successful trials often take longer to enroll patients than planned. Recent findings show that AI-based methods have been effective in identifying eligible participants for trials by using both imaging and text data. Therefore, the article suggests that those conducting trials should consider using AI-powered tools to enhance future studies.
Outcomes and Implications
The primary implication for the medical field is that artificial intelligence can serve as a powerful tool to overcome major barriers in clinical research, potentially making trials faster, cheaper, and more successful. By automating the finding of eligible participants, AI can make the recruitment process easier, which causes many trials to fail or run over budget. This suggests that researchers across various specialties, not just ophthalmology, could accelerate the development and approval of new therapies, ultimately allowing the medical community to deliver innovative treatments to patients more quickly. For this to be implemented, however, it would necessitate a greater focus on creating standardized, high-quality electronic health records and imaging databases.