Predicting functional impairment trajectories in amyotrophic lateral sclerosis: a probabilistic, multifactorial model of disease progression
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R. Rinaldi | B. Di Camillo | M. Vinceti | A. Borghi | R. Michelucci | A. Chiò | G. Mora | V. Drory | A. Calvo | G. Pavesi | P. Ghiglione | P. Cortelli | S. Meletti | E. Sette | M. Pugliatti | N. Di Vito | C. Moglia | F. Valzania | E. Zucchi | I. Martinelli | J. Mandrioli | M. Gotkine | M. C. Torrieri | U. Manera | A. Canosa | R. Vasta | G. Fuda | M. Grassano | P. Cugnasco | N. Launaro | L. Mazzini | I. Bartolomei | N. Fini | S. D'alfonso | D. Leotta | G. Gusmaroli | C. Comi | A. Bertolotto | L. Corrado | L. Testa | C. Lunetta | M. Brunetti | F. Casale | F. Marchi | M. Bracaglia | M. De Mattei | M. Barberis | B. Iazzolino | L. Peotta | F. Palumbo | V. Vacchiano | C. Tarlarini | S. Vidale | Alessandro Zandonà | M. Casmiro | C. Labate | L. Sbaiz | B. Nefussy | S. Gallone | A. Sapio | Fabrizio Salvi | F. Poglio | C. Simonini | G. Gianferrari | M. Santangelo | A. Patuelli | E. Canali | D. Ferrandi | E. Terlizzi | M. Aguggia | P. Meineri | S. Malagù | L. Zinno | M. Longoni | S. Morresi | A. Bombaci | E. Tavazzi | Sebastian Daberdaku | A. Rita Levi A. C. A. U. R. F. A. M. M. F. G. P. B. L Chiò Montalcini Calvo Moglia Canosa Manera Vas | R. L. Montalcini | S. Gentile | A. Mauro | M. Gionco | E. Oddenino | R. Cavallo | L. Ruiz | E. Rota | M. Dotta | M. Giovanni | R. Liguori | A. Zini | V. Tugnoli | L. Codeluppi | D. Medici | G. Pilurzi | D. Guidetti | S. Pasqua | P. Querzani | M. Currò Dossi | G. D. De Marco | Enrico Grisan | P. Salomone | P. DeMassis | M. Curro’ Dossi | E. Grisan | A. Chiò | P. Querzani
[1] D. Fan,et al. Prognostic models for amyotrophic lateral sclerosis: a systematic review , 2021, Journal of Neurology.
[2] P. Bede,et al. Manifold learning for amyotrophic lateral sclerosis functional loss assessment , 2020, Journal of Neurology.
[3] Enrico Longato,et al. A practical perspective on the concordance index for the evaluation and selection of prognostic time-to-event models , 2020, J. Biomed. Informatics.
[4] A. Chiò,et al. A Dynamic Bayesian Network model for the simulation of Amyotrophic Lateral Sclerosis progression , 2019, BMC Bioinformatics.
[5] Ivo D Dinov,et al. Model-Based and Model-Free Techniques for Amyotrophic Lateral Sclerosis Diagnostic Prediction and Patient Clustering , 2018, Neuroinformatics.
[6] Karel G M Moons,et al. Prognosis for patients with amyotrophic lateral sclerosis: development and validation of a personalised prediction model , 2018, The Lancet Neurology.
[7] Jung-Hsien Chiang,et al. Stratification of amyotrophic lateral sclerosis patients: a crowdsourcing approach , 2018, Scientific Reports.
[8] E. Granieri,et al. Riluzole and other prognostic factors in ALS: a population-based registry study in Italy , 2018, Journal of Neurology.
[9] Adriano Chiò,et al. Secular Trends of Amyotrophic Lateral Sclerosis: The Piemonte and Valle d’Aosta Register , 2017, JAMA neurology.
[10] G. Nagel,et al. Hypothalamic atrophy is related to body mass index and age at onset in amyotrophic lateral sclerosis , 2017, Journal of Neurology, Neurosurgery, and Psychiatry.
[11] A. Chiò,et al. Age-related penetrance of the C9orf72 repeat expansion , 2017, Scientific Reports.
[12] Mei-Lyn Ong,et al. Predicting functional decline and survival in amyotrophic lateral sclerosis , 2017, PloS one.
[13] A. Al-Chalabi,et al. Comparison of the King’s and MiToS staging systems for ALS , 2017, Amyotrophic lateral sclerosis & frontotemporal degeneration.
[14] Alberto Franzin,et al. bnstruct: an R package for Bayesian Network structure learning in the presence of missing data , 2016, Bioinform..
[15] A. Al-Chalabi,et al. Amyotrophic lateral sclerosis: moving towards a new classification system , 2016, The Lancet Neurology.
[16] Neta Zach,et al. Predicting disease progression in amyotrophic lateral sclerosis , 2016, Annals of clinical and translational neurology.
[17] Jj Allaire,et al. Web Application Framework for R , 2016 .
[18] Pedro Tomás,et al. Prognostic models based on patient snapshots and time windows: Predicting disease progression to assisted ventilation in Amyotrophic Lateral Sclerosis , 2015, J. Biomed. Informatics.
[19] Claudio Cobelli,et al. A Dynamic Bayesian Network model for long-term simulation of clinical complications in type 1 diabetes , 2015, J. Biomed. Informatics.
[20] E. Granieri,et al. Heterogeneity in ALSFRS-R decline and survival: a population-based study in Italy , 2015, Neurological Sciences.
[21] F. Franchignoni,et al. A further Rasch study confirms that ALSFRS-R does not conform to fundamental measurement requirements , 2015, Amyotrophic lateral sclerosis & frontotemporal degeneration.
[22] A. Chiò,et al. The MITOS system predicts long-term survival in amyotrophic lateral sclerosis , 2015, Journal of Neurology, Neurosurgery & Psychiatry.
[23] Dimitrios I. Fotiadis,et al. A Multiscale Approach for Modeling Atherosclerosis Progression , 2015, IEEE Journal of Biomedical and Health Informatics.
[24] M. Cudkowicz,et al. The PRO-ACT database , 2014, Neurology.
[25] Johann S. Hawe,et al. Crowdsourced analysis of clinical trial data to predict amyotrophic lateral sclerosis progression , 2014, Nature Biotechnology.
[26] Hans H. Jung,et al. RandomForest4Life: A Random Forest for predicting ALS disease progression , 2014, Amyotrophic lateral sclerosis & frontotemporal degeneration.
[27] E. Granieri,et al. Epidemiology of amyotrophic lateral sclerosis in Emilia Romagna Region (Italy): A population based study , 2014, Amyotrophic lateral sclerosis & frontotemporal degeneration.
[28] Maurizio Fava,et al. Amyotrophic lateral sclerosis disease progression model , 2014, Amyotrophic lateral sclerosis & frontotemporal degeneration.
[29] V. Meininger,et al. A phase II−III trial of olesoxime in subjects with amyotrophic lateral sclerosis , 2014, European journal of neurology.
[30] A. Al-Chalabi,et al. Use of clinical staging in amyotrophic lateral sclerosis for phase 3 clinical trials , 2014, Journal of Neurology, Neurosurgery & Psychiatry.
[31] Adriano Chiò,et al. State of play in amyotrophic lateral sclerosis genetics , 2013, Nature Neuroscience.
[32] A. Chiò,et al. Development and evaluation of a clinical staging system for amyotrophic lateral sclerosis , 2013, Journal of Neurology, Neurosurgery & Psychiatry.
[33] O. Hardiman,et al. Dexpramipexole versus placebo for patients with amyotrophic lateral sclerosis (EMPOWER): a randomised, double-blind, phase 3 trial , 2013, The Lancet Neurology.
[34] E. Beghi,et al. Randomized double-blind placebo-controlled trial of acetyl-L-carnitine for ALS , 2013, Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration.
[35] A. Chiò,et al. Evidence of multidimensionality in the ALSFRS-R Scale: a critical appraisal on its measurement properties using Rasch analysis , 2013, Journal of Neurology, Neurosurgery & Psychiatry.
[36] A. Al-Chalabi,et al. Young-onset amyotrophic lateral sclerosis: historical and other observations. , 2012, Brain : a journal of neurology.
[37] A. Al-Chalabi,et al. The genetics and neuropathology of amyotrophic lateral sclerosis , 2012, Acta Neuropathologica.
[38] R. Spataro,et al. Factors affecting the diagnostic delay in amyotrophic lateral sclerosis , 2012, Clinical Neurology and Neurosurgery.
[39] Janel O. Johnson,et al. Frequency of the C9orf72 hexanucleotide repeat expansion in patients with amyotrophic lateral sclerosis and frontotemporal dementia: a cross-sectional study , 2012, The Lancet Neurology.
[40] A. Al-Chalabi,et al. A proposed staging system for amyotrophic lateral sclerosis , 2012, Brain : a journal of neurology.
[41] A. Chiò,et al. ALS clinical trials , 2011, Neurology.
[42] A. Chiò,et al. Phenotypic heterogeneity of amyotrophic lateral sclerosis: a population based study , 2011, Journal of Neurology, Neurosurgery & Psychiatry.
[43] Pamela A McCombe,et al. Effects of gender in amyotrophic lateral sclerosis. , 2010, Gender medicine.
[44] I. Mackenzie,et al. TDP-43 and FUS in amyotrophic lateral sclerosis and frontotemporal dementia , 2010, The Lancet Neurology.
[45] M. Turner,et al. The diagnostic pathway and prognosis in bulbar-onset amyotrophic lateral sclerosis , 2010, Journal of the Neurological Sciences.
[46] P. Berlit,et al. Diagnostic problems and delay of diagnosis in amyotrophic lateral sclerosis , 2010, Clinical Neurology and Neurosurgery.
[47] Nir Friedman,et al. Probabilistic Graphical Models - Principles and Techniques , 2009 .
[48] M. Massagli,et al. Measuring function in advanced ALS: validation of ALSFRS‐EX extension items , 2009, European journal of neurology.
[49] A. Voustianiouk,et al. ALSFRS and appel ALS scores: Discordance with disease progression , 2008, Muscle & nerve.
[50] Xun Hu,et al. TDP-43 Mutations in Familial and Sporadic Amyotrophic Lateral Sclerosis , 2008, Science.
[51] Constantin F. Aliferis,et al. The max-min hill-climbing Bayesian network structure learning algorithm , 2006, Machine Learning.
[52] S H Appel,et al. Forced vital capacity (FVC) as an indicator of survival and disease progression in an ALS clinic population , 2005, Journal of Neurology, Neurosurgery & Psychiatry.
[53] K. Talbot. Motor neuron disease , 2004, Practical Neurology.
[54] A. Al-Chalabi,et al. Early symptom progression rate is related to ALS outcome: a prospective population-based study. , 2002, Neurology.
[55] M. Swash,et al. El Escorial revisited: Revised criteria for the diagnosis of amyotrophic lateral sclerosis , 2000, Amyotrophic lateral sclerosis and other motor neuron disorders : official publication of the World Federation of Neurology, Research Group on Motor Neuron Diseases.
[56] J. Cedarbaum,et al. The ALSFRS-R: a revised ALS functional rating scale that incorporates assessments of respiratory function , 1999, Journal of the Neurological Sciences.
[57] R. Tibshirani. The lasso method for variable selection in the Cox model. , 1997, Statistics in medicine.
[58] P. Leigh,et al. Motor neuron disease. , 1994, Springer London.
[59] D. Silberberg,et al. New diagnostic criteria for multiple sclerosis: Guidelines for research protocols , 1983, Annals of neurology.
[60] N. Pearce,et al. The multistep hypothesis of ALS revisited , 2018, Neurology.
[61] A. Al-Chalabi,et al. Amyotrophic lateral sclerosis , 2017, Nature Reviews Disease Primers.
[62] A. Chiò,et al. Factors predicting survival in ALS: a multicenter Italian study , 2016, Journal of Neurology.
[63] A. Ludolph,et al. Amyotrophic lateral sclerosis. , 2012, Current opinion in neurology.
[64] A. Brunetti,et al. A randomized controlled clinical trial of growth hormone in amyotrophic lateral sclerosis: clinical, neuroimaging, and hormonal results , 2011, Journal of Neurology.
[65] Jürgen Hesser,et al. Virtual Intensive Care Unit (ICU): Real-Time Simulation Environment Applying Hybrid Approach Using Dynamic Bayesian Networks and ODEs , 2009, MMVR.
[66] D. Rosen. Mutations in Cu/Zn superoxide dismutase gene are associated with familial amyotrophic lateral sclerosis , 1993, Nature.