References
- Bionetworks, S., (2020). Sage Bionetworks”, Synapse. [Online]. [Accessed: 30 January 2020], synapse ID: syn20681023. https://www.synapse.org/#!Synapse:syn20681023/wiki/
- Brooks, D. J., and N. Pavese. 2011. Imaging biomarkers in Parkinson’s disease. Progress in Neurobiology 95 (4):614–28. doi:https://doi.org/10.1016/j.pneurobio.2011.08.009.
- Emamzadeh, F. N., and A. Surguchov. 2018. Parkinson’s disease: Biomarkers, treatment, and risk factors. Frontiers in Neuroscience 12: 612. eCollection 2018. doi:https://doi.org/10.3389/fnins.2018.00612.
- Erik, Z., R. Maud, A. Elodie, C. Tim, S. Johan, B. Evelyne, P. Christophe, and G. Gaëtan. 2014. Mapping track density changes in nigrostriatal and extranigral pathways in Parkinson’s disease. Neuroimage 99:498–508.
- Graziella, O., P. Y. William, F. M. Andre, S. Giuseppe, and M. Andrea. 2012. Using support vector machine to identify imaging biomarkers of neurological and psychiatric disease: A critical review. Neuroscience and Biobehavioral Reviews 36 (4):1140–52.
- Hamza, T. H., and H. Payami. 2010. The heritability of risk and age at onset of Parkinson’s disease after accounting for known genetic risk factors. Journal of Human Genetics 55 (4):241–43. doi:https://doi.org/10.1038/jhg.2010.13.
- Harith, A., W. Chengyuan, H. Jonathan, F. Thomas, L. Patricia, D. V. Enrico, Y. Tarek, J. Marjan, H. Marwan, B. Timothy, et al. 2017. L-Dopa responsiveness is associated with distinctive connectivity patterns in advanced Parkinson’s disease. Movement Disorders 32 (6):874–83. doi:https://doi.org/10.1002/mds.27017.
- Hawkins, D. M., C. Basak, and D. M. Mills. 2003. Assessing model fit by cross-validation. Journal of Chemical Information and Computer Sciences 43 (2):579–86. doi:https://doi.org/10.1021/ci025626i.
- He, R., X. Yan, J. Guo, Q. Xu, B. Tang, and Q. Sun. 2018. Recent advances in biomarkers for Parkinson’s disease. Frontiers in Aging Neuroscience 10: 305. eCollection 2018. doi:https://doi.org/10.3389/fnagi.2018.00305.
- Jankovic, J. 2008. Parkinson’s disease: Clinical features and diagnosis. Journal of Neurology, Neurosurgery & Psychiatry 79 (4):368–76. doi:https://doi.org/10.1136/jnnp.2007.131045.
- Khoo, T. K., J. Y. Alison, W. Gordon, S. C. Duncan, T. O. B. John, J. B. David, A. Roger, and D. J. B. Barker. 2013. The spectrum of nonmotor symptoms in early Parkinson disease. Neurology 80 (3):276–81.
- Kim Jae, W., V. Sharma, and N. D. Ryan. 2015. Predicting methylphenidate response in ADHD using machine learning approaches. International Journal of Neuro-psychopharmacology 18 (11):1–7. doi:https://doi.org/10.1093/ijnp/pyv052.
- Klein, C., and A. Westenberger. 2012. Genetics of Parkinson’s disease. Cold Spring Harbor Perspectives in Medicine 2 (1):a008888. PMID: 22315721; PMCID: PMC3253033. doi:https://doi.org/10.1101/cshperspect.a008888.
- Lang Anthony, E., and M. L. Andres. 1998. Parkinson’s disease. New England Journal of Medicine 339 (16):1130–43.
- Luo, C. Y., S. Wei, C. Qin, Z. Zhen, C. Ke, C. Bei, Y. Jing, P. L. Jian, H. Xiao, G. QiYong, et al. 2014. Reduced functional connectivity in early-stage drug-naive Parkinson’s disease: A resting-state fMRI study. Neurobiology of Aging 35 (2):431–41.
- McGuire, L. I., H. P. Alexander, D. O. Christina, M. W. Jason, E. A. Nigel, M. Gary, A. Mary, W. H. Mark, C. Byron, G. W. Robert, et al. 2012. Real time quaking-induced conversion analysis of cerebrospinal fluid in sporadic Creutzfeldt-Jakob disease. Annals of Neurology 72 (2):278–85.
- The Michael J. Fox Foundation for Parkinson’s Research, Parkinson’s Disease (2020). Dyskinesia. [online]. [Accessed 1 August 2020]. https://www.michaeljfox.org/news/dyskinesia
- Movement Disorder Society Task Force on Rating Scales for Parkinson’s Disease. 2003. The unified Parkinson’s disease rating scale (UPDRS): Status and recommendations. Movement Disorders 18(7): 738–50. PMID: 12815652. doi:https://doi.org/10.1002/mds.10473.
- Poewe, W., A. Angelo, C. M. Z. Jan, R. B. Pierre, and V. François. 2010. Levodopa in the treatment of Parkinson’s disease: An old drug still going strong. Clinical Interventions in Aging 5:229–38.
- Rao, S. S., A. H. Laura, and S. Amer. 2006. Parkinson’s disease: Diagnosis and treatment. American Family Physician 74 (12):2046–54.
- Ritika, A., H. R. Bullah, A. Prabhakar, A. Jatain, S. B. Bajaj, and V. Jaglan. 2020. Parkinson’s disease: Taking a Step towards Homogenizing Machine Leaning and Medical Science. International Journal of Psychosocial Rehabilitation 24 (4):6558–69. doi:https://doi.org/10.37200/IJPR/V24I4/PR2020466.
- Ron, K., and H. J. George. 1997. Wrappers for feature subset selection. Artificial Intelligence 97 (2):273–324.
- Thanvi, B. R., and T. C. N. Lo. 2004. Long term motor complications of levodopa: Clinical features, mechanisms, and management strategies. Postgraduate Medical Journal 80 (946):452–58. doi:https://doi.org/10.1136/pgmj.2003.013912.
- Zlotnik, A., M. M. Juan, S. S. Rubén, and G. A. Ascensión (2015). Random forest-based prediction of Parkinson’s disease progression using acoustic, ASR and intelligibility features. In the proceedings of ‘Sixteenth Annual Conference of the International Speech Communication Association. Interspeech, Dresden, Germany: 503–07.