Implementation of Machine Learning (ML) in Biomedical Engineering

Abstract

The subfields within AI have been discussed throughout the article and the findings of the article have provided a positive outcome. ML has a huge potential through ML methodologies such as supervised and unsupervised learning as discussed in the article. However, supervised learning requires only labeled data while unsupervised learning has the potential to identify the hidden characteristics of the data. The clinical predictors that have been provided through "NN model" and "DT model" have the potential through determining the small datasets within biomedical engineering that further helps medical practitioners or healthcare professionals to decide on the medicine and treatment required for a patient. Keyword : Biomedical Engineering, Machine Learning, ML Model, Nanoscale.