| Literature DB >> 32669685 |
Monika A Myszczynska1, Poojitha N Ojamies2, Alix M B Lacoste3, Daniel Neil2, Amir Saffari2, Richard Mead1, Guillaume M Hautbergue1, Joanna D Holbrook2, Laura Ferraiuolo4.
Abstract
Globally, there is a huge unmet need for effective treatments for neurodegenerative diseases. The complexity of the molecular mechanisms underlying neuronal degeneration and the heterogeneity of the patient population present massive challenges to the development of early diagnostic tools and effective treatments for these diseases. Machine learning, a subfield of artificial intelligence, is enabling scientists, clinicians and patients to address some of these challenges. In this Review, we discuss how machine learning can aid early diagnosis and interpretation of medical images as well as the discovery and development of new therapies. A unifying theme of the different applications of machine learning is the integration of multiple high-dimensional sources of data, which all provide a different view on disease, and the automated derivation of actionable insights.Entities:
Mesh:
Year: 2020 PMID: 32669685 DOI: 10.1038/s41582-020-0377-8
Source DB: PubMed Journal: Nat Rev Neurol ISSN: 1759-4758 Impact factor: 42.937