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Parkinson's disease (keyword)
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1
book article
Detailed analysis of the Luria's alternating series tests for Parkinson's disease diagnostics
Nõmm, Sven
;
Bardõš, Konstantin
;
Toomela, Aaro
;
Medijainen, Kadri
;
Taba, Pille
17th IEEE International Conference on Machine Learning and Applications : ICMLA 2018, 17–20 December 2018, Orlando, Florida, USA : proceedings
2018
/
p. 1347–1352
https://doi.org/10.1109/ICMLA.2018.00219
book article
2
book article
Interpretable quantitative description of the digital clock drawing test for Parkinson's disease modelling
Nõmm, Sven
;
Mašarov, Ilja
;
Toomela, Aaro
;
Medijainen, Kadri
;
Taba, Pille
15th International Conference on Control, Automation, Robotics and Vision (ICARCV 2018) : Singapore, November 18-21, 2018
2018
/
p. 1839-1844 : ill
https://doi.org/10.1109/ICARCV.2018.8581074
book article
3
journal article
Intrastriatally infused exogenous CDNF is endocytosed and retrogradely transported to substantia nigra
Mätlik, Kert
;
Vihinen, Helena
;
Bienemann, Ali
;
Palgi, Jaan
;
Arumäe, Urmas
eNeuro
2017
/
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 diagnostics
Wang, Xuechao
;
Huang, Junqing
;
Chatzakou, Marianna
;
Medijainen, Kadri
;
Taba, Pille
;
Toomela, Aaro
;
Nõmm, Sven
;
Ruzhansky, Michael
36th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2023, Aquila, 22-24 June 2023
2023
/
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 disease
Voutilainen, Merja H.
;
Arumäe, Urmas
;
Airavaara, Mikko
;
Saarma, Mart
FEBS letters
2015
/
p. 3739-3748 : ill
http://dx.doi.org/10.1016/j.febslet.2015.09.031
journal article
Number of records 5, displaying
1 - 5
keyword
47
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 heart disease
17.
disease
18.
disease diagnosis
19.
disease model
20.
disease models
21.
disease resistance
22.
end stage renal disease
23.
end-stage kidney disease
24.
garment workers and patients with occupational disease
25.
heart disease risk factors
26.
Huntington’s disease
27.
infectious disease
28.
in-transit disease
29.
late blight disease
30.
loco-regionally metastatic disease
31.
lyme disease
32.
mechanisms of disease
33.
Menkes disease
34.
molecular bases of disease
35.
NAFLD (non-alcoholic fatty liver disease)
36.
neurodegenerative disease
37.
neuromuscular disease
38.
non-alcoholic fatty liver disease
39.
oat striate and red disease
40.
physical overload disease
41.
preclinical Alzheimer disease
42.
renal disease
43.
stable coronary heart disease
44.
subclinical cardiovascular disease
45.
Wilson disease
46.
Wilson’s disease
47.
von Willebrand disease
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