Ensemble learning predicts multiple sclerosis disease course in the SUMMIT study

[1]  B. Malomed,et al.  A new form of liquid matter: Quantum droplets , 2020, Frontiers of Physics.

[2]  X. Montalban,et al.  SUMMIT (Serially Unified Multicenter Multiple Sclerosis Investigation): creating a repository of deeply phenotyped contemporary multiple sclerosis cohorts , 2018, Multiple sclerosis.

[3]  Tie-Yan Liu,et al.  LightGBM: A Highly Efficient Gradient Boosting Decision Tree , 2017, NIPS.

[4]  Tianqi Chen,et al.  XGBoost: A Scalable Tree Boosting System , 2016, KDD.

[5]  Rushi Longadge,et al.  Class Imbalance Problem in Data Mining Review , 2013, ArXiv.

[6]  E. Mowry Natural history of multiple sclerosis: early prognostic factors. , 2011, Neurologic clinics.

[7]  B. Brochet Expanded Disability Status Scale (EDSS) , 2009, Multiple Sclerosis.

[8]  Carrilin C. Trecker,et al.  Reduction of disease activity and disability with high-dose cyclophosphamide in patients with aggressive multiple sclerosis. , 2008, Archives of neurology.

[9]  Ludwig Kappos,et al.  Effect of early versus delayed interferon beta-1b treatment on disability after a first clinical event suggestive of multiple sclerosis: a 3-year follow-up analysis of the BENEFIT study , 2007, The Lancet.

[10]  Susan A Gauthier,et al.  A model for the comprehensive investigation of a chronic autoimmune disease: the multiple sclerosis CLIMB study. , 2006, Autoimmunity reviews.

[11]  S. Vukusic,et al.  Age at disability milestones in multiple sclerosis. , 2006, Brain : a journal of neurology.

[12]  Rodney X. Sturdivant,et al.  Applied Logistic Regression: Hosmer/Applied Logistic Regression , 2005 .

[13]  P. Adeleine,et al.  Early clinical predictors and progression of irreversible disability in multiple sclerosis: an amnesic process. , 2003, Brain : a journal of neurology.

[14]  S. Copt,et al.  Generalized Linear Models , 2001 .

[15]  Thomas G. Dietterich Multiple Classifier Systems , 2000, Lecture Notes in Computer Science.

[16]  Corinna Cortes,et al.  Support-Vector Networks , 1995, Machine Learning.

[17]  D. Wolpert Original Contribution: Stacked generalization , 1992 .

[18]  B Bass,et al.  The natural history of multiple sclerosis: a geographically based study. 2. Predictive value of the early clinical course. , 1989, Brain : a journal of neurology.

[19]  B Bass,et al.  The natural history of multiple sclerosis: a geographically based study. I. Clinical course and disability. , 1989, Brain : a journal of neurology.

[20]  J. Ross Quinlan,et al.  Induction of Decision Trees , 1986, Machine Learning.

[21]  J. Kurtzke Rating neurologic impairment in multiple sclerosis , 1983, Neurology.

[22]  Stacked Generalization , 2017, Encyclopedia of Machine Learning and Data Mining.

[23]  Didrik Nielsen,et al.  Tree Boosting With XGBoost - Why Does XGBoost Win "Every" Machine Learning Competition? , 2016 .

[24]  P. Vermersch,et al.  Natural history of multiple sclerosis with childhood onset. , 2007, The New England journal of medicine.

[25]  L. Breiman Random Forests , 2001, Machine Learning.

[26]  M. Amato,et al.  A prospective study on the prognosis of multiple sclerosis , 2000, Neurological Sciences.

[27]  Yoav Freund,et al.  A Short Introduction to Boosting , 1999 .