Abstract
Over the past decade, healthcare tools leveraging artificial intelligence and machine learning have transitioned from academic-centered development to industry. Key drivers include limited funding, rising computational requirements, and an exodus of academic talent to industry. The ramifications of this are both significant and concerning. Strategies should focus on sharing capital, talent, and advisory boards across industry and academia to foster innovation that is clinically relevant and impactful.