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.

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.

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

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!

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.

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?

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.

@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.

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.

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.

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.

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.

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.

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.

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

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

May have been in the training data.

Nice app. But wouldn't a doctor normally get a history as well? Anyway, I'm not a doctor which is probably why I got most of the answers wrong :)

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

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.

I don't fucking care if we all lose our jobs, as long as we also fuck the VCs by making them obsolete.

Think a set number of questions to start with would be good. Not sure if there’s an end point, I drifted off after ~20 or so

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

Idea: distribution of player scores

I'm going to get some models checked out.

https://share.icloud.com/photos/048Y_ALNTMwlP3QqZNwja5HEQ

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

For personal fulfillment, humanities evolutionary fitness, and for commercial purposes

"Vibe coded" - asked ChatGPT or whatever alternative to do the thing for me. There is no fucking vibe here, just another cheesy term.