In this paper, we introduce a new concept called Artificial Special Intelligence by which Machine Learning models for the classification problem can be trained error-free, thus acquiring the capability of not making repeated mistakes. The method is applied to 18 MedMNIST biomedical datasets. Except for three datasets, which suffer from the double-labeling problem, all are trained to perfection.
@article{arxiv.2604.18916,
title = {Benchmarking PNW Model for MedMNIST to 100% Accuracy},
author = {Bo Deng},
journal= {arXiv preprint arXiv:2604.18916},
year = {2026}
}