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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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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 EST / journal article ENG

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 https://doi.org/10.1523/ENEURO.0128-16.2017 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

journal article EST / journal article ENG
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. end-stage renal disease
27. garment workers and patients with occupational disease
28. genetic predisposition to disease
29. heart disease risk factors
30. Huntington’s disease
31. infectious disease
32. in-transit disease
33. late blight disease
34. loco-regionally metastatic disease
35. lyme disease
36. mechanisms of disease
37. Menkes disease
38. molecular bases of disease
39. NAFLD (non-alcoholic fatty liver disease)
40. neurodegenerative disease
41. neuromuscular disease
42. non-alcoholic fatty liver disease
43. oat striate and red disease
44. physical overload disease
45. preclinical Alzheimer disease
46. renal disease
47. stable coronary heart disease
48. subclinical cardiovascular disease
49. Wilson disease
50. Wilson’s disease
51. von Willebrand disease

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