Improving Cancer Imaging Diagnosis with Bayesian Networks and Deep Learning: A Bayesian Deep Learning Approach

arXiv:2403.19083v1 Announce Type: new
Abstract: With recent advancements in the development of artificial intelligence applications using theories and algorithms in machine learning, many accurate models can be created to train and predict on given datasets. With the realization of the importance of imaging interpretation in cancer diagnosis, this article aims to investigate the theory behind Deep Learning and Bayesian Network prediction models. Based on the advantages and drawbacks of each model, different approaches will be used to construct a Bayesian …

abstract algorithms applications artificial artificial intelligence arxiv bayesian bayesian deep learning cancer cs.ai cs.lg datasets deep learning development diagnosis eess.iv imaging importance improving intelligence interpretation machine machine learning networks train type