A Artificial intelligence and neuroscience: A systematic review

Abstract

Abstract
In critical fields like medicine and healthcare, the transparency and comprehensibility of machine learning and artificial intelligence systems hold immense importance in garnering trust in their outcomes. Errors stemming from these systems, such as incorrect diagnoses or treatments, bear the potential for serious, even life-threatening repercussions for patients. Consequently, Artificial Intelligence (AI) has emerged as a pivotal area of investigation, focusing on unraveling the opaque nature of intricate and challenging-to-comprehend machine learning models. While human expertise can enhance the accuracy of these models, comprehending the inner workings of these models during their training phase can prove challenging, if not impossible. In our research, we identified 211 articles published in 2023 and delved into 20 of them to examine the application of these methodologies within the medical domain.
Key words: Machine learning, Artificial intelligence, Neuroscience, Neural networks