Artificial Intelligence shaping the future of neurology practice

Clinical Applications of Artificial Intelligence—An Updated Overview

“…Machine learning (ML) Process by which an algorithm encodes statistical regularities from a database of examples into parameter weights for future predictions [11] Deep learning (DL) Multilayered complex ML platform comprised of numerous computational layers able to make accurate predictions [6] Supervised learning Training an ML algorithm using previously labeled training examples, consisting of inputs and desired outputs provided by an expert [7,11] Figure 1. Relationship between AI, ML, and DL.…”

“…Unsupervised learning When an ML algorithm discovers hidden patterns or data groupings without the need for human intervention [11] Reinforcement learning…”

“…Learning strategies towards acting optimally in certain situations with respect to a given criterion; such an algorithm obtains feedback on its performance by comparison with this criterion through reward values during training [7] Model A trained ML algorithm that can make predictions from unseen data [11] Training Feeding an ML algorithm with examples from a training dataset towards deriving useful parameters for future predictions [11] Features Components of a dataset describing the characteristics of the studied observations [1] Decision tree Nonparametric supervised learning method visualized as a graph representing the choices and their outcomes in the form of a tree; each tree consists of nodes (attributes in the group to be classified) and branches (values that a node can take) [12,13] Random forest Ensemble classification technique that uses "parallel ensembling", fitting several decision tree classifiers in parallel on dataset subsamples [13] Naïve Bayes (NB)…”

“…An ML technique that processes information in an architecture comprising many layers ("neurons"), each inter-neuronal connection extracting the desired parameters incrementally from the training data [6,11] Deep neural network (DNN) A DL architecture with multiple layers between the input and output layers [11] Convolutional neural network (CNN)…”

“…A class of DNN displaying connectivity patterns similar to the connectivity patterns and image processing in the visual cortex [11] In recent years, AI has attracted more and more research interest in medicine, being investigated for a plethora of applications. Numerous studies have evaluated various aspects of the healthcare system, reporting the progress in AI involvement in the prevention, screening, and treatment of diseases and prediction of the prognosis [14,15].…”