Big data, machine learning and artificial intelligence: a neurologist's guide. Issue 1 (29th September 2020)

• Record Type: Journal Article
• Authors: Auger, Stephen D; Jacobs, Benjamin M; Dobson, Ruth; Marshall, Charles R; Noyce, Alastair J
• Is Part Of: Practical neurology. Volume 21:Issue 1(2021)
• Page Start: 4
• Page End: 11
• Publication Date: 2020-09-29
• Subjects: Neuroradiology -- image analysis -- health policy & practice -- evidence-based neurology -- clinical neurology; Neurology -- Periodicals; 616.8005
• DOI: 10.1136/practneurol-2020-002688
• Languages: English
• ISSNs: 1474-7758

Abstract

Abstract : Modern clinical practice requires the integration and interpretation of ever-expanding volumes of clinical data. There is, therefore, an imperative to develop efficient ways to process and understand these large amounts of data. Neurologists work to understand the function of biological neural networks, but artificial neural networks and other forms of machine learning algorithm are likely to be increasingly encountered in clinical practice. As their use increases, clinicians will need to understand the basic principles and common types of algorithm. We aim to provide a coherent introduction to this jargon-heavy subject and equip neurologists with the tools to understand, critically appraise and apply insights from this burgeoning field.