Neurological Therapeutics
Online ISSN : 2189-7824
Print ISSN : 0916-8443
ISSN-L : 2189-7824
 
Clinical applications of artificial intelligence
Genko OyamaNobutaka Hattori
Author information
JOURNAL FREE ACCESS

2024 Volume 41 Issue 4 Pages 485-487

Details
Abstract

Artificial Intelligence (AI) is a computer program designed to mimic human intelligence by performing functions such as learning, reasoning, and judgment. At the core of AI is machine learning, which includes supervised learning―where models learn from labeled data―and unsupervised learning, which involves identifying patterns and classifying data without labeled examples. A key component of machine learning is neural networks, inspired by human neurons arranged in layers to form a network. Deep learning is a more advanced form of neural network, which involves networks with multiple layers that have significantly enhanced AI capabilities.

AI has found applications in a wide range of medical fields, particularly in diagnosing and treating neurological disorders, accelerating rapidly. While AI's use in neuroimaging analysis is well–established, recent advancements have expanded its applications to include automatic speech recognition and natural language processing for conducting patient interviews, as well as the digitization of neurological assessments through wearable devices and video motion analysis. These advancements have made it possible to analyze neurological signs that were previously challenging to assess with AI.

Additionally, there is growing interest in using AI to analyze multi–omics data for identifying biochemical biomarkers from biological samples, such as blood and cerebrospinal fluid. With the continued evolution of AI, more accurate and predictive diagnoses are anticipated.

Content from these authors
© 2024 Japanese Society of Neurological Therapeutics
Previous article Next article
feedback
Top