So over the last few months, I've been working on an AI model that could classify a skin lesion as cancerous or not using only an image of the lesion. At first, I thought there's no way that I could achieve anything more than 70% accuracy but after tweaking with my program for a long while, I was able to reach an accuracy of over 95% which is definitely an improvement compared to my first tries.
The other day, I was talking to a professor at my local university whom I've written a paper with and showed him my classifier. He told me that I could write a paper on it which had never come to my mind because I believe an accuracy of 95% is not nearly good enough and the methods that I used weren't new, cutting edge methods that could have a huge impact in the AI industry.
Fast forward a couple days, I found all the papers related to classifying skin lesions using ML and DL and I actually found quite a few but they all are vastly different from my model(different hyperparameters, the different architectures, different models, etc) but the accuracy in all of them are pretty close to mine(they were all very close to 95%).
My question is, do you think it's worth it to even try and write a paper about my work or is it pointless and won't help me in the future?
P.S: I've already read a similar question but that was about research in math which is VERY different. In math, the solution is sometimes more important than the finding but I'm not sure if that's the case with AI.
By the way, I'm 14, so I'm not sure whether I can do this independently or not.
Thank you so, so much!