Random forest modelling of neuropathological features identifies microglial activation as an accurate pathological classifier of C9orf72-related amyotrophic lateral sclerosis
Olivia M. Rifai, James Longden, Judi O’Shaughnessy, Michael D.E. Sewell, Judith A. Pate, Karina McDade, Michael J. D. Daniels, Sharon Abrahams, Siddharthan Chandran, Barry W. McColl, Christopher R. Sibley, Jenna M. Gregory
The paper uses random forest modelling to identify microglial activation as a key classifier for C9orf72-related ALS and shows spatial FUS staining changes predict disease status.
The Journal of Pathology · Sep 7, 2022Peer-reviewedNeuroscience