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422 points sungam | 1 comments | | HN request time: 0.208s | 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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vindex10 ◴[] No.45158481[source]
Hi! That's really useful tool!

I wish it also explained the decision making process, how to understand from the picture what is the right answer.

I'm really getting lost between melanoma and seborrheic keratosis / nevus.

I went through ~120 pictures, but couldn't learn to distinguish those.

Also, the guide in the burger menu leads to a page that doesn't exist: https://molecheck.info/how-to-recognise-skin-cancer

replies(3): >>45159338 #>>45161189 #>>45167123 #
sungam ◴[] No.45159338[source]
This is very helpful feedback. I will add some more information to help with the diagnosis and add an article in the burger menu with detailed explanation.

Being honest I didn't expect anyone apart from a few of may patients to use the app and certainly did not expect front page HN!

replies(1): >>45161212 #
1. jgilias ◴[] No.45161212[source]
Hey!

Thanks for making this! A bit more polish and this is something I’d make sure everyone in my family has played with.

Imagine a world where every third person is able to recognise worrying skin lesions early on.