# Longitudinal scans can track changes across hundreds of moles

Markdown copy of https://realalpha.app/s/longitudinal-scans-can-track-changes-across-hundreds-of/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy.

- Speaker: [Daniel Ek](https://realalpha.app/people/daniel-ek/) · Daniel Ek is a Spotify cofounder and executive chairman; Neko Health cofounder. · Co-founded Spotify in 2006 and now guides its long-term strategy as executive chairman.
- Host: [Chamath Palihapitiya](https://realalpha.app/people/chamath-palihapitiya/) · Founder & CEO, Social Capital · Led Facebook's growth team; his firm backed Slack and AI chipmaker Groq.
- Host: [Jason Calacanis](https://realalpha.app/people/jason-calacanis/) · Founder & CEO, LAUNCH · Early Uber angel; sold Weblogs Inc. to AOL; hosts This Week in Startups.
- Host: [David Sacks](https://realalpha.app/people/david-sacks/) · Co-founder & partner, Craft Ventures · PayPal's first COO, founded Yammer; White House AI & crypto czar 2025–26.
- Host: [David Friedberg](https://realalpha.app/people/david-friedberg/) · CEO, Ohalo · Founded The Climate Corporation, sold to Monsanto for about $1.1B in 2013.
- Show: All-In
- Episode: [Daniel Ek: Life After Spotify, Broken Healthcare Incentives, Catching Disease Early & AI's Potential](https://realalpha.app/v/JEUboZzZGM4/), Sep 28, 2026
- Moment: 19:37 to 22:15 of the episode (3 min), playing on https://realalpha.app/s/longitudinal-scans-can-track-changes-across-hundreds-of/; the episode from there: https://realalpha.app/v/JEUboZzZGM4/?t=1177

## Quote

> “The average person at NECO today has **950 moles**. It's pretty crazy.”
> — [Daniel Ek](https://realalpha.app/people/daniel-ek/) at [19:45](https://realalpha.app/v/JEUboZzZGM4/?t=1185) · All-In

## Takeaways

1. Neko members average about 950 moles.
2. AI flags possible risks, then clinicians review them.
3. Repeat scans can reveal abnormal growth over time.

## About this segment

Daniel Ek says Neko scans and indexes skin marks, with AI flagging possible risks for clinicians to review. Comparing scans over time may reveal changes a doctor could not reliably remember.

From “Daniel Ek: Life After Spotify, Broken Healthcare Incentives, Catching Disease Early & AI's Potential”, Sep 28, 2026. [Watch the full episode](https://realalpha.app/v/JEUboZzZGM4/)

## Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

[19:39](https://realalpha.app/v/JEUboZzZGM4/?t=1179) So it's really kind of all across the basis, but I'll give you a very concrete example. So take dermatology as a great example. The average person at NECO today has 950 moles. It's pretty crazy. The average person has 950 moles? Yes. That's insane. You can't tell, I guess, is the punchline here. They're like not detectable by the human eye. For sure. Well, if you really went through your skin, you'd be surprised how many you'd find.

[20:09](https://realalpha.app/v/JEUboZzZGM4/?t=1209) I mean, it's a big dispersion. Some have, you know, many, many thousands and some of them have 500. Seems like a perfect AI application for AI, obviously. Exactly. So if you think about it across a normal doctor's visit, how likely is it that that doctor will check out all the 950 moles that you may have? It's not going to happen. So normally what happens in a normal doctor visit would be, you may say, look, I have a mole or the doctor sees, hey, let's take a look at that mole.

[20:39](https://realalpha.app/v/JEUboZzZGM4/?t=1239) It looks a little bit funky. And then they bring out their tool where they inspect it. They usually these days have a software that checks against whether this mole, they take a camera across many different frequencies to then discover both the size of this mole, but also the texture of the mole and so on and so forth. We literally do that. And we first have an AI system that flag possible risk factors.

[21:07](https://realalpha.app/v/JEUboZzZGM4/?t=1267) And then we have a human clinician that then goes through and reviews those as well. And should we even at that point find something, we then have expert dermatologists on staff, multiple of them that then also reviews that result. So that's just one indicator of like what happens in one visit. But let's now presume the scenario that we'd have multiple visits. And maybe one year, it's actually, we don't discover anything.

[21:32](https://realalpha.app/v/JEUboZzZGM4/?t=1292) But because we've cataloged and indexed every single one, we can actually now, in a longitudinal base, look at them from one year to the next year. So it may be growing abnormally. These are things that if you think about it, even the best doctors in the world can't possibly remember how your mole may have looked like from one year to another. So again, back to your point, this is a perfect application of AI, right?

[21:58](https://realalpha.app/v/JEUboZzZGM4/?t=1318) But we look at this as like, this is a perfect application of how healthcare should look like. It should seamlessly be both AI and amazing clinicians in a great package experience. So that's essentially what we're trying to do with NetGo. That's great.