Qompass AI is designed with equal access in mind. The included codebases (see below) support amplifying human intelligence across the medical education community and focus on a variety of topics relevant to AI development and implementation, providing the community with a foundation to safely navigate this work. The codebases offer alignment with regulatory guidelines and industry and academic best practices across the domains of security, education, deployment, and infrastructure. By providing adaptable, open-source solutions, Qompass AI charts a course towards empowering clinical learners and educators to safely navigate the implementation of AI in a cost effective way.
Qompass AI Github Homepage
Quality AI Security Solutions
Quality AI Education Solutions
Quality AI Deployment Solutions
Quality AI MicroServer Solutions
Authors
Matt A. Porter, Founder/CEO, Qompass AI
Ariana Rowshan, Orthopaedic Research Fellow, Johns Hopkins University School of Medicine
Dawn Laporte, MD, FAAOS, Orthopaedic Residency Program Directory, Johns Hopkins University School of Medicine
Amiethab A. Aiyer, MD, FAAOS, Foot & Ankle Service Chief, Associate Professor, Department of Orthopaedics, Johns Hopkins University School of Medicine