Demographically-Conditioned Synthetic Medical Images for Bias Mitigation and Bia
Per-subgroup fairness audits of medical image classifiers face a sample-size problem: minority subgroups in held-out test sets have so few samples that the resulting confidence intervals on per-subgroup performance are wider than the bias t
https://arxiv.org/abs/2607.14984v1 ↗Thesis fit
Good fit
Within your typical scope; diligence still required.
In your usual scope
Idea match
Light
How close the company’s idea is to your thesis statement
Sector
ai
Overlap with sectors you care about
Geography
Outside
Outside your target regions — scores 0
Your thesis: “We back exceptional technical founders building AI-first products and infrastructure, deploying $100K checks within 24 hours.”
Founder → stable
Traction → stable
Idea vs market ↓ declining
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Correct facts used on the next screening or memo.
People
M
Mahmoud Ibrahim
2.0
low confidence
B
Bart Elen
4.6
low confidence
C
Chang Sun
2.0
low confidence
G
Gokhan Ertaylan
1.0
low confidence
M
Michel Dumontier
2.0
low confidence
G
Gökhan Ertaylan
BE
1.0
low confidence
Activity & evidence
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