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

(molecheck.info)
422 points sungam | 2 comments | 07 Sep 25 10:38 UTC | HN request time: 0.536s | 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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lazarus01 ◴[07 Sep 25 15:35 UTC] No.45159105[source]▶
What you created is a version of “am I hot or not” for skin cancer. The idea is constrained to the limitations of your programming capability. Showing a photo and creating 3 buttons with a static response is not very helpful. These are the limits of vibe coding.

I was thinking to train a convnet to accurately classify pictures of moles as normal vs abnormal. The user can take a photo and upload it to a diagnostic website and get a diagnosis.

It doesn’t seem like an overly complex model to develop and there is plenty of data referring to photos that show normal vs abnormal moles.

I wonder why a product hasn’t been developed, where we are using image detection on our phones to actively screen for skin cancer. Seems like a no brainer.

My thinking is there are not enough deaths to motivate the work. Dying from melanoma is nasty.

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1. sungam ◴[07 Sep 25 15:51 UTC] No.45159263[source]▶
The goal of my app is to educate patients so that they recognise that they need to take further action.

Regarding AI-assisted skin cancer diagnosis: This is a huge area that started with the publication of Esteva et al (https://www.nature.com/articles/nature21056) and there have been hundreds of publications since. There are large publicly available datasets that anyone can work with (https://challenge.isic-archive.com/).

My lab has previously trained / evaluated convnets for diagnosis of skin cancer e.g. see this publication: https://pubmed.ncbi.nlm.nih.gov/32931808/

I have no doubt that it will be possible to train an AI model to perform at the same level as a dermatologist and AI models will become increasingly relevant. The main challenge at the moment is navigating uncertainty / liability since a very small proportion of moles / skin lesions that appear entirely harmless both the naked eye and with the dermatoscope (skin microscope) are cancerous.

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2. lazarus01 ◴[07 Sep 25 16:10 UTC] No.45159448[source]▶
Thanks for including those information resources. This is something I’m interested in digging deeper into.