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Show HN: I'm a dermatologist and I vibe coded a skin cancer learning app

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422 points sungam | 2 comments | 07 Sep 25 10:38 UTC | HN request time: 0.578s | source

Coded using Gemini Pro 2.5 (free version) in about 2-3 hours.

Single file including all html/js/css, Vanilla JS, no backend, scores persisted with localStorage.

Deployed using ubuntu/apache2/python/flask on a £5 Digital Ocean server (but could have been hosted on a static hosting provider as it's just a single page with no backend).

Images / metadata stored in an AWS S3 bucket.

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jjallen ◴[07 Sep 25 13:21 UTC] No.45157933[source]▶
Very cool. I learned a lot as a non dermatologist but someone with a sister who has had melanoma at a very young age.

I went from 50% to 85% very quickly. And that’s because most of them are skin cancer and that was easy to learn.

So my only advice would be to make closer to 50% actually skin cancer.

Although maybe you want to focus on the bad ones and get people to learn those more.

This was way harder than I thought this detection would be. Makes me want to go to a dermatologist.

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1. loeg ◴[07 Sep 25 19:44 UTC] No.45161503[source]▶
I found the first dozen to be mostly cancer and then the next dozen were mostly non-cancer. (Not sure if it's randomized.) (Also, I'm really bad at identifying cancerous vs non-cancerous skin lesions.)
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2. sungam ◴[07 Sep 25 20:08 UTC] No.45161684[source]▶
It is randomized so probably just bad luck! FWIW I get a high score and another skin cancer doctor who commented also gets a high score so it is possible to make the diagnosis in most cases on the basis of these images.