AI-Powered Residency Screening: How RankRX Uses LLMs to Fix Unfair Application Filtering
Delta: HealthTech Innovators · Roupen Odabashian
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Show Notes
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