AI-Powered Residency Screening: How RankRX Uses LLMs to Fix Unfair Application Filtering

​MalkeAsaad, plastic surgery resident and founder of Rank RX, shares how he built an AI platform using large language models to revolutionize residency application screening. From med school in war-torn Aleppo to Mayo Clinic and MD Anderson, Malke discusses the unfair filtering system that inspired Rank RX—where Nobel Prize laureates get rejected for missing a cutoff by one point—and how AI can make hiring more objective and efficient.

What you'll learn:

- Why the current residency application system is broken (Nobel Prize winner rejected for 1-point score gap)

- How Rank RX uses AI/LLMs to screen 1,000–2,000 applications (30–80 pages each) in minutes

- Building a tech team as a physician entrepreneur without coding background

- Customer acquisition strategies for healthcare startups (networking, ads, v ...