Identifying multiple sclerosis subtypes using unsupervised machine learning and MRI data - Eshaghi, Arman; Young, Alexandra L.; Wijeratne, Peter A.; Prados, Ferran; Arnold, Douglas L.; Narayanan, Sridar; Guttmann, Charles R. G.; Barkhof, Frederik; Alexander, Daniel C.; Thompson, Alan J.; Chard, Declan; Ciccarelli, Olga (Nature communications, 2021)
Keywords: 631/114/116/2396; 631/1647/245/1627; 631/378/1689/1666; 692/699/375/1411/1666; Abnormalities; Adult; Algorithms; Autoimmune diseases; Clinical trials; Databases as Topic; Disease Progression; Female; Health services; Humanities and Social Sciences; Humans; Learning algorithms; Lesions; Machine learning; Magnetic Resonance Imaging; Male; Medical imaging; Middle Aged; Models, Biological; Multidimensional data; multidisciplinary; Multiple sclerosis; Multiple Sclerosis - diagnosis; Multiple Sclerosis - diagnostic imaging; Neuroimaging; Patients; Phenotypes; Placebos; Randomized Controlled Trials as Topic; Recurrence; Reproducibility of Results; Science; Science (multidisciplinary); Substantia alba; Unsupervised learning; Unsupervised Machine Learning