___

[1] Kaynak Selekler (2010). Alois alzheimer ve alzheimer hastalığı. Türk Geriatri Dergisi. Vol. 13. Pages. 9-14.

[2] Nadire Özaras and Selim Yalçın (2002). Normal yürüme ve yürüme analizi. Turkish Journal of Physical Medicine and Rehabilitation. Vol. 48(3).

[3] National Collaborating Centre for Chronic Conditions (2006). Parkinson's Disease: National Clinical Guideline for Diagnosis and Management in Primary and Secondary Care. London, UK: Royal College of Physicians.

[4] Jeffrey M. Bronstein, Michele Tagliati, Ron L. Alterman, Andres M. Lozano, Jens Volkmann, Alessandro Stefani, Fay B. Horak, Michael S. Okun, Kelly D. Foote, Paul Krack, Rajesh Pahwa, Jaimie M. Henderson, Marwan I. Hariz, Roy A. Bakay, Ali Rezai, William J. Marks, Elena Moro, Jerrold L. Vitek, Frances M. Weaver, Robert E. Gross and Mahlon R. DeLong (2011). Deep brain stimulation for Parkinson disease: an expert consensus and review of key issues. Arch. Neurol. Vol. 68 (2). Pages. 165.

[5] Samuel Frank and Joseph Jankovic (2010). Advances in the pharmacological management of huntington's disease. Drugs. Vol. 70(5). Pages. 561-571.

[6] Patrick Russell and Roger Harrison (2014). What is amyotrophic lateral sclerosis?. Clinical Pharmacist. Vol. 6(7).

[7] Masood Banaie, Mohammad Pooyan and Mohammad Mikaili (2011). Introduction and application of an automatic gait recognition method to diagnose movement disorders that arose of similar causes. Expert Systems with Applications. Vol. 38(6). Pages. 7359-7363.

[8] Mohammad R. Daliri (2012). Automatic diagnosis of neurodegenerative diseases using gait dynamics. Measurement. Vol. 45(7). Pages. 1729-1734.

[9] Sang-Hong Lee and Joon S. Lim (2012). Parkinson’s disease classification using gait characteristics and wavelet-based feature extraction. Expert Systems with Applications. Vol. 39(8). Pages. 7338-7344.

[10] Drotár, P., Mekyskaa, J., Rektorováb, I., Masarováb, L., Smékala, Z. ve Faundez-Zanuyc, M. 2014. “Analysis of inair movement in handwriting:A novel marker for Parkinson’s disease”, Computer Methods and Programs in Biomedicine, 117(3), 405 411.

[11] Akdemir, Ü.Ö., Tokçaer, B., Karakuş, A. ve Kapucu, L.Ö. 2014. “Brain 18F-FDG PET Imaging in the Differential Diagnosis of Parkinsonism”, Clinical Nuclear Medicine, 93(3), 220 226.

[12] Lee, S., Kim, M., Lee, H.M., Kwona, K., Kim, H. ve Koh, S. 2014. “Differential diagnosis of parkinsonism with visual inspection of posture and gait in the early stage”, Gait & Posture, 39(4), 1138 1141.

[13] Pilleri, M., Levedianos, G., Weis, L., Gasparoli, E., Facchini, S., Biundo, R., Formento-Dojot, P. ve Antonini, A. 2014. “Heart rate circadian profile in the differential diagnosis between Parkinson disease and multiple system atrophy”, Parkinsonism and Related Disorders, 20(2), 217 221.

[14] Navarro-Otano, J., Gaig, C., Muxi, A., Lomeña, F., Compta, Y., Buongiorno, M.T., Martí, M.J., Tolosa, E. ve Valldeoriola, F. 2014. “123I-MIBG cardiac uptake, smell identification and 123I-FP-CIT SPECT in the differential diagnosis between vascular parkinsonism and Parkinson’s disease”, Parkinsonism and Related Disorders, 20(2), 192 197.

[15] Salvatorea, C., Cerasab, A., Castiglioni, I., Gallivanonec, F., Augimerib, A., Lopezd, M., Arabiae, G., Morellie, M., Gilardi, M.C. ve Quattrone, A. 2014. “Machine learning on brain MRI data for differential diagnosis of Parkinson’s disease and Progressive Supranuclear Palsy”, Journal of Neuroscience Methods, 222, 230 237.

[16] Yi Xia, Qingwei Gao and Qiang Ye (2015). Classification of gait rhythm signals between patients withneuro-degenerative diseases and normal subjects: Experiments withstatistical features and different classification models. Biomedical Signal Processing and Control. Vol. 18. Pages. 254-262.

[17] Feng, J., Huang, B., Yang, W., Zhang, Y., Wang, L., Wang, L. ve Zhong, X. 2014. “The putaminal abnormalities on 3.0T magnetic resonance imaging: can they separate parkinsonism-predominant multiple system atrophy from Parkinson’s disease?”, Acta radiologica, 56(3), 322 328.

[18] Baudrexel, S., Seifried, C., Penndorf, B., Klein, J.C., Middendorp, M., Steinmetz, H., Grünwald, F. Ve Hilker, R. 2014. “The Value of Putaminal Diffusion Imaging Versus

18-Fluorodeoxyglucose Positron Emission Tomography for the Differential Diagnosis of the Parkinson Variant of Multiple System Atrophy”, Movement Disorders, 29(3), 380 387.

[19] Huertas-Fernández, I., García-Gómez, F.J., García-Solís, D., Benítez-Rivero, S., Marín-Oyaga, V.A., Jesús, S., CáceresRedondo, M.T., Lojo, J.A., Martín-Rodríguez, J.F., Carrillo, F. ve Mir, P. 2015. “Machine learning models for the differential diagnosis of vascular parkinsonism and Parkinson’s disease using [123I]FP-CIT SPECT”, European journal of nuclear medicine and molecular imaging, 42(1), 112 119.

[20] Zanigni, S., Testa, C., Calandra-Buonaura, G., Sambati, L., Guarino, M., Gabellini, A., Evangelisti, S., Cortelli, P., Lodi, R. ve Tonon, C., 2015. “The contribution of cerebellar proton magnetic resonance spectroscopy in the differential diagnosis among parkinsonian syndromes”, Parkinsonism and Related Disorders, 21(8), 929 937.

[21] Bradvica, I.S., Mihaljevic´, I., Butkovic´-Soldo, S., Kadojic´, D., Titlic´, M., Bradvica, M. ve Kralik, K. 2015.

“Transcranial sonography and the pocket smell test in the differential diagnosis between parkinson’s disease and essential tremor”, Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology, 36(8), 1403 1410.

[22] Vranová, H.P, Hényková, E., Mareš, J., Kaiserová, M., Menšíková, K., Vaštík, M., Hluštík, P., Zapletalová, J., Strnadb, M., Stejskal, D. ve Kaňovský, P. 2016. “Clusterin CSF levels in differential diagnosis of neurodegenerative disorders”, Journal of the Neurological Sciences, 361, 117 121.

[23] Drotár, P., Mekyska, J., Rektorová, I., Masarová, L., Smékal, Z. ve Faundez-Zanuy, M. 2016. “Evaluation of handwriting kinematics and pressure for differentialdiagnosis of Parkinson’s disease”, Artificial Intelligence in Medicine, 67, 39 46.

[24] PhysioNET. Gait Dynamics in Neuro-Degenerative Disease Data Base. http://www.physionet.org/physiobank/database/gaitndd/. [Accessed: 13.04.2015].

[25] Jeffrey M. Hausdorff, Zvi Ladin and Jeanne Y. Wei (1995). Footswitch system for measurement of the temporal parameters of gait. J Biomech. Vol. 28(3). Pages. 347–351.

[26] Jeffrey M. Hausdorff, Susan L. Mitchell, Renee Firtion, Chung-Kang Peng, Merit E. Cudkowicz, Jeanne Y. Wei and Ary L. Goldberger (1997). Altered fractal dynamics of gait: reduced stride-interval correlations with aging and huntington's disease. J Applied Physiology. Vol. 82(1). Pages. 262-269.

[27] Jeffrey M. Hausdorff, Apinya Lertratanakul, Merit E. Cudkowicz, Amie L. Peterson, David Kaliton and Ary L. Goldberger (2000). Dynamic markers of altered gait rhythm in amyotrophic lateral sclerosis. J Applied Physiology. Vol. 88. Pages. 2045-2053.

[28] Pamela K. Douglas, Sam Harris, Alan L. Yuille and Mark S. Cohen (2011). Performance comparison of machine learning algorithms and number of independent components used in fMRI decoding of belief vs. disbelief. NeuroImage. Vol. 56(2). Pages. 544-553.

[29] Ian H. Witten and Eibe Frank (2005). Data Mining: Practical Machine Learning Tools and Techniques. 2nd ed. San Francisco, CA, USA: Morgan Kaufmann.

[30] Stuart J. Russell and Peter Norvig (2003). Artificial Intelligence: A Modern Approach. 2nd ed. Upper Saddle River, New Jersey, USA: Prentice Hall.

[31] Pedro Domingos (2000). A unifed bias-variance decomposition and its applications, In: Proceedings of the Seventeenth International Conference on Machine Learning, 29 June-2 July 2000; Stanford, CA, USA. San Francisco, CA, USA: Morgan Kaufmann. pp. 231-238.