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book article

Detailed analysis of the Luria's alternating series tests for Parkinson's disease diagnosticsNõmm, Sven; Bardõš, Konstantin; Toomela, Aaro; Medijainen, Kadri; Taba, Pille17th IEEE International Conference on Machine Learning and Applications : ICMLA 2018, 17–20 December 2018, Orlando, Florida, USA : proceedings2018 / p. 1347–1352 https://doi.org/10.1109/ICMLA.2018.00219

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book article

Interpretable quantitative description of the digital clock drawing test for Parkinson's disease modellingNõmm, Sven; Mašarov, Ilja; Toomela, Aaro; Medijainen, Kadri; Taba, Pille15th International Conference on Control, Automation, Robotics and Vision (ICARCV 2018) : Singapore, November 18-21, 20182018 / p. 1839-1844 : ill https://doi.org/10.1109/ICARCV.2018.8581074

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journal article

Intrastriatally infused exogenous CDNF is endocytosed and retrogradely transported to substantia nigraMätlik, Kert; Vihinen, Helena; Bienemann, Ali; Palgi, Jaan; Arumäe, UrmaseNeuro2017 / art. e0128-16.2017, p. 1-15 : ill http://dx.doi.org/10.1523/ENEURO.0128-16.2017

journal article
4

book article EST / book article ENG

A light-weight CNN model for efficient Parkinsons disease diagnosticsWang, Xuechao; Huang, Junqing; Chatzakou, Marianna; Medijainen, Kadri; Taba, Pille; Toomela, Aaro; Nõmm, Sven; Ruzhansky, Michael36th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2023, Aquila, 22-24 June 20232023 / p. 616-621 https://doi.org/10.1109/CBMS58004.2023.00289 Conference proceedings at Scopus Article at Scopus Article at WOS

book article EST / book article ENG
5

journal article

Therapeutic potential of the endoplasmic reticulum located and secreted CDNF/MANF family of neurotrophic factors in Parkinson's diseaseVoutilainen, Merja H.; Arumäe, Urmas; Airavaara, Mikko; Saarma, MartFEBS letters2015 / p. 3739-3748 : ill http://dx.doi.org/10.1016/j.febslet.2015.09.031

journal article

Number of records 5, displaying 1 - 5

1. Parkinson's disease
2. Parkinson’s disease
3. Parkinson’s disease machine learning
4. Parkinson disease
5. Parkinson’s diseas
6. Alzheimer’s disease
7. Alzheimer's disease
8. anti-GBM disease
9. cardiovascular disease
10. celiac disease
11. cerebrovascular disease
12. chronic kidney disease
13. chronic obstructive pulmonary disease
14. coronary artery disease
15. coronary artery disease (CAD)
16. coronary disease
17. coronary heart disease
18. disease
19. disease diagnosis
20. disease model
21. disease models
22. disease progression
23. disease resistance
24. end stage renal disease
25. end-stage kidney disease
26. garment workers and patients with occupational disease
27. genetic predisposition to disease
28. heart disease risk factors
29. Huntington’s disease
30. infectious disease
31. in-transit disease
32. late blight disease
33. loco-regionally metastatic disease
34. lyme disease
35. mechanisms of disease
36. Menkes disease
37. molecular bases of disease
38. NAFLD (non-alcoholic fatty liver disease)
39. neurodegenerative disease
40. neuromuscular disease
41. non-alcoholic fatty liver disease
42. oat striate and red disease
43. physical overload disease
44. preclinical Alzheimer disease
45. renal disease
46. stable coronary heart disease
47. subclinical cardiovascular disease
48. Wilson disease
49. Wilson’s disease
50. von Willebrand disease

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