ALL-SAFE Case Study
High-Tech, AI-Enhanced Surgical Training for Low Resource Settings.
Introduction
ALL-SAFE, a leader in global surgical education and the grand prize winner of the Global Surgical Training Challenge, collaborated with Abstract Partners to develop a cutting-edge surgical training platform. This platform, enhanced with AI for analyzing laparoscopic skill videos, aims to make high-quality surgical education accessible worldwide, particularly in low- and middle-income countries, including those in Africa, which bears 25% of the world’s burden of surgical disease with only 2% of the global health workforce.
Challenges
Lean Validation Development: Engaged in the Global Surgical Training Challenge's three rounds, the project required phased validation without fully developing the entire product experience.
Asynchronous Learners: The primary peer review learning method encountered difficulties due to dependency on learners.
Strategic Solutions
Platform for Global Reach and Accessibility: Utilizing an open-source LMS platform accelerated deployment, incorporating advanced features to deliver quality surgical training in areas with low connectivity or offline.
Scalability and Efficiency: Our AI model, leveraging both structured and deep learning, has been trained across four distinct surgical modules. This advanced training enables the model to deliver assessments in near-real-time. This innovation significantly reduces the dependency on synchronous learner participation and the continuous creation of new training videos, streamlining the deployment of new training modules.
Outcomes & Conclusion
Awarded the Grand Prize in the Global Surgical Training Challenge, totaling $1.75 million in prize grants
Hundreds of trainees have successfully completed the courses, leading to the adoption and increase of laparoscopic surgical procedures in participating hospitals
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