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, vendor screening)

- Market validation: assessing if your solution solves a real problem people will pay for

Timestamps

- 0:00 – Unfair residency filtering: Nobel Prize winner rejected for 1-point gap

- 1:14 – Malke Assad’s journey: From Aleppo to leading U.S. institutions

- 3:45 – Rank RX: How AI/LLMs bring objectivity to application screening

- 4:21 – How it works: Custom scoring and program-driven selection criteria

- 8:36 – Real-world usage: Positive feedback and automated recommendation letter analysis

- 10:32 – Building a tech team without a coding background

- 17:35 – Key advice for physician entrepreneurs: Turning ideas into scalable companies

- RankRX Website: https://www.rank-rx.com/

- Malke Assad LinkedIn: https://www.linkedin.com/in/malke-asaad-43b908177

- The Match Guy Website: https://thematchguy.thinkific.com