Cargando…
Harnessing the potential of machine learning and artificial intelligence for dementia research
Progress in dementia research has been limited, with substantial gaps in our knowledge of targets for prevention, mechanisms for disease progression, and disease-modifying treatments. The growing availability of multimodal data sets opens possibilities for the application of machine learning and art...
Autores principales: | Ranson, Janice M., Bucholc, Magda, Lyall, Donald, Newby, Danielle, Winchester, Laura, Oxtoby, Neil P., Veldsman, Michele, Rittman, Timothy, Marzi, Sarah, Skene, Nathan, Al Khleifat, Ahmad, Foote, Isabelle F., Orgeta, Vasiliki, Kormilitzin, Andrey, Lourida, Ilianna, Llewellyn, David J. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9958222/ https://www.ncbi.nlm.nih.gov/pubmed/36829050 http://dx.doi.org/10.1186/s40708-022-00183-3 |
Ejemplares similares
-
Artificial Intelligence for Dementia Research Methods Optimization
por: Bucholc, Magda, et al.
Publicado: (2023) -
Cardiometabolic multimorbidity, genetic risk, and dementia: a prospective cohort study
por: Tai, Xin You, et al.
Publicado: (2022) -
Socioeconomic Deprivation, Genetic Risk, and Incident Dementia
por: Klee, Matthias, et al.
Publicado: (2023) -
Parathyroid Hormone, Cognitive Function and Dementia: A Systematic Review
por: Lourida, Ilianna, et al.
Publicado: (2015) -
Harnessing Transcriptomic Signals for Amyotrophic Lateral Sclerosis to Identify Novel Drugs and Enhance Risk Prediction
por: Pain, Oliver, et al.
Publicado: (2023)