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

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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.

I kind of love the diy aspect of ai coding.

A dermatologist a short while ago with this idea would have to find a willing and able partner to do a bunch of work -- meaning that most likely it would just remain an idea.

This isn't just for non-tech people either -- I have a decades long list of ideas I'd like to work on but simply do not have time for. So now I'm cranking up the ol' AI agents an seeing what I can do about it.

4 days agoby jmull

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.

4 days agoby jjallen

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

4 days agoby vindex10

I'm a doctor too and would love to hear more about the rationale and process for creating this.

It's quite interesting to have a binary distinction: 'concerned vs not concerned', which I guess would be more relevant for referring clinicians, rather than getting an actual diagnosis. Whereas naming multiple choice 'BCC vs melanoma' would be more of a learning tool useful for medical students..

Echoing the other comments, but it would be interesting to match the cards to the actual incidence in the population or in primary care - although it may be a lot more boring with the amount of harmless naevi!

4 days agoby lukko

Nice job. Now you really need to study up on the statistics behind this and you'll quickly come to the conclusion that this was the easy part. What to do with the output is the hard part. I've seen a start-up that made their bread and butter on such classifications, they did an absolutely great job of it but found the the problem of deciding what to do with such an application without ending up with net negative patient outcomes to be far, far harder than the classification problem itself. The error rates, no matter how low, are going to be your main challenge, both false positives and false negatives can be extremely expensive, both in terms of finance and in terms of emotion.

4 days agoby jacquesm

This is awesome. Great use of AI to realize an idea. Subject matter experts making educational tools is one of the most hopeful things to come out of AI.

It’s just a bummer that it’s far more frequently used to pump wealth to tech investors from the entire class of people that have been creating things on the internet for the past couple of decades, and that projects like this fuel the “why do you oppose fighting cancer” sort of counter arguments against that.

4 days agoby DrewADesign

As someone with literally every single possible variation of skin blemish, mole and God knows what else, this scares the living hell out of me.

3 days agoby globalise83

Is this really "invasive melanoma"? https://drmagnuslynch.s3.eu-west-2.amazonaws.com/isic-images...

4 days agoby meindnoch

Perfect use of AI assisted coding - a domain expert creating a focused, relatively straightforward (from a programming perspective) app.

@sungam, if your research agenda includes creating AI models for skin cancer, feel free to reach out (email in profile), I make a tool intended to help pure clinical researchers incorporate AI into their research programmes.

4 days agoby rfrey

Cool project, and helpful for learning.

One concern:

I don't believe the rates that you see "concerning" vs "not-concerning" in the app match the population rates. That is, a random "mole-like spot or thingy" on a random person will have have a much lower base rate of being cancerous than the app would suggest.

Of course, this is necessary to make the learning efficient. But unless you pair it with base rate education it will create a bias for over-concern.

4 days agoby jonahx

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.

4 days agoby lazarus01

I like the project! Congrats on the launch.

As I understand it, size is one of the key indicators of melanoma. But in some of these images, it’s difficult to tell whether the mole is 1 mm or 10 mm. I assume your image set doesn’t include size information. If you can find sources with rulers or some kind of scale, that would be very helpful.

4 days agoby andreasgl

Every image with a pen marking is dangerous/cancer. Check.

4 days agoby omer9

Biggest irony of the thread is the OP and the ones commenting celebrating the tech putting themselves out of the job while contributing it. Eg. a dermatologist who looks at skin conditions -- a very visual skill. They use their skills at that to build an app that people can use to check for skin cancer, rashes, whatever. Now, people have less incentive to see a dermatologist and might miss the zebras (and in fact: people are lazy and tend to hate doctors already so they won't.) Then there's the software engineers here who (even if you're a high level senior engineer) are further moved down the chopping board the better AI gets.

YAY, three cheers for all the soy boys building AI. See you on unemployment soon.

3 days agoby Uptrenda

To my eye most of the basal cell carsinomas looked like everyday rashes, pimples or scratches. My correct rate was under chance. This could be hypochondria inducing for many?

4 days agoby jampekka

Vibe coding is like spreadsheets.

We take spreadsheet for granted. VisiCalc back in the day unlocked computing for an average person in the same way AI does today. Back then to tabulate some stats you’d need a team of programmers. When spreadsheets became available, anyone could figure out how to essentially program a computer without software background.

It would be interesting to see how spreadsheets failed/succeeded to learn the limits of vibe coding. For example it’s a common meme that you find teams using spreadsheets as databases. Perhaps they are so successful that they end up being misused. Would the same happen with AI coding?

3 days agoby softwaredoug

I’ve learned that basal cell carcinoma can look scarily unremarkable!

Would be useful to add some explanation on the defining features that would give it away to a dermatologist.

4 days agoby rcruzeiro

This is a good use of vibecoding. The main "algorithm" to be implemented is very straightforward , and for the hard stuff, we have an expert.

4 days agoby agnishom

(spoilers!) here's how to win: everything is cancer, except the common moles and the keratoses.

OP, what are some of the other common options for a spot on the body aside from common moles, cancer, and keratoses? Solar lentigines, freckles, bug bites, eczema? I'm also curious what the actual chance of cancer is given a random mole anywhere on the body, obviously a more involved question.

4 days agoby owenversteeg

A few years ago there used to be an ML-based app for Android that could classify photos of lesions that you took with your phone and could recommend you a visit to the dermatologist (or not). Unfortunately it seems to be removed now, the webpage is still live (somewhat): https://emdee.ai/

It was done by a small team in Hungary, with the support of MDs of course. (I would guess that the majority of the work was coordinating with MDs, getting them to teach the software... and collecting photos of lesions. Must have been fun!)

They probably could not monatize it (or were not interested, or it was just too much work for a side hustle)... the sad reality of living in Eastern Europe.

I do think that the idea is perfect, it is non-invasive, but could warn you of a potentially very dangerous condition in time. You don't have to wait for the doctor, or unnecessarily visit them. I would actually pay for this as a service.

4 days agoby haspok

This just highlights that domain experts became even more valuable with LLMs. Not only they know the domain, now they realise their ideas too with minor effort. Doesn't bode well for programmers in non-tech areas.

3 days agoby noisy_boy

Half of these basal cell carcinomas look like picked pimples. Are there any sort of protocols for self screening for carcinomas a la self-testing ones testicles? I've never heard of anything other than the ABCDE for moles

4 days agoby y-curious

This project really resonates with me. I have a few friends in healthcare who had great ideas for patient tools, but without a technical partner and no budget for a development team, nothing ever came of them.

Seeing someone actually build something like this, even if it's not perfect, gives me a sense of hope. When you combine domain expertise with some AI tools, you don’t have to wait around for someone else. You can just start.

3 days agoby zoeey

This was always the dream for people with real ideas for an app but lacked the knowhow to build it.

Namely: “I have an idea for an app but I don’t know how to do it and I don’t want to spend all my time and resources on the app either. The app is a means to an end, not the end itself.”

We are now living in a time where getting to the end is much more possible.

3 days agoby thr0waway001

There may be an interesting opportunity to gather data on the accuracy of guesses per image. You could use something like Google analytics, but simple server-side logging is more private and keeps the page light.

The question could be: What images are most often mistaken? What characteristics do they share? Knowing the highest false negative images would be really valuable people to know what not to ignore.

3 days agoby reilly3000

Is there any reputable (reviewed, endorsed) AI model to detect skin cancer? I have a lot of similar moles, and playing with this app make me concern about all of them.

4 days agoby toledocavani

This is great, I had no idea how off base I was with my assumptions. It’ll be interesting to keep the usage data to find out what kinds of images people have the most trouble with. As in what kind of mole is the most likely to be missed. Though perhaps dermatologist already know that answer well enough.

I would love to see more of such classifiers for other medical conditions, googling for images tends not to produce a representative sample.

4 days agoby cjbgkagh

Wow this game just proves to me how difficult your job is. I am basically getting 50%.

One or two seemed quite obvious to me as concerning or not but turned out to be the other way

4 days agoby k2xl

Are there an equal amount of cancer and non cancer images? In my case the vast majority (I'd say around 75%) are cancerous.

4 days agoby redox99

Why do the images get a weird offset slice effect on safari on mobile after submitting a guess with the buttons?

4 days agoby leetrout

Thank you for making this.

My dad passed away from squamous cell carcinoma in 2010. In retrospect, through my casual research into the space and tools like this one, it occurs to me that the entire event was likely preventable and occurred merely because we did not react quickly enough to the cancer’s presence.

4 days agoby ziptron

You've really had a great idea, and maybe you can save lives with this. Do you process the images yourself? Do you pass them to some AI? How does it work for privacy? Do you delete them afterwards? Thanks and congratulations.

3 days agoby 8mobile

This is actually a really great vibe coded app. It's simple and doesn't require much logic. Will vibe coding catch on to more sophisticated and complex use cases? That's only if the whispers about an upcoming AI Winter are false.

3 days agoby kittikitti

Good example of shovelware that some say is absent.¹

¹ https://mikelovesrobots.substack.com/p/wheres-the-shovelware...

4 days agoby m-hodges

I just opened this up to see if HN was supportive or hyper-critical of vibe coding in medicine.

Since this isn't invasive I'm glad to see its the supportive option.

3 days agoby AbstractH24

The hamburger menu "About" and "How To Recognize Skin Cancer" both go to a 404 page that's a copy of a company website called "Revessa Health". Is this your company?