Scientific paper that studies the impact of different machine learning algorithms for the prediction of diagnosis and dysplasia Status

We implemnt the following algorithms:

-ARTIFICIAL NEURAL NETWORK (ANN) ALGORITHM

-DECISION TREE (DT) ALGORITHM

-K-NEAREST NEIGHBORS (K-NN) ALGORITHM

We managed to show that 3 (three) algorithms in machine learning can be used to support the predictive accuracy of a data set. Despite the challenges and barriers above, the potential for ML-based AI approaches to digital diagnosis is promising because AI has strong feature representation learning capabilities made possible by improved algorithms, big data accumulation and increased computing power. People will have more confidence in AI algorithms once they have been validated using multi-center data and have increased interpretability. Collaboration between diagnostic experts and AI will promote more precise treatment for many patients in healthcare.