scholarly journals Revisiting the question of psoriasis classification

2021 ◽  
Vol 97 (5) ◽  
pp. 18-25
Author(s):  
A. E. Karamova ◽  
O. Y. Olisova ◽  
A. L. Bakulev ◽  
M. M. Kokhan ◽  
V. R. Khairutdinov ◽  
...  
Keyword(s):  
Psoriatic Arthritis ◽  
Diagnostic Process ◽  
Clinical Classification ◽  
Common Understanding

Currently there are a large number of psoriasis classifications, slightly different from each other, used worldwide. Some of these classifications contain the disease forms allocated descriptively, without the pathogenesis characteristics in their basis. Among the dermatologists, there is lack of common understanding of various psoriasis forms peculiarities. And that affects both the diagnostic process and the approaches to therapy. The authors propose a revised unified clinical classification of psoriasis, including psoriatic arthritis. This method reflects the up-to-date view on the classification of psoriasis in Russia and globally.

Clinical classification of hyperuricemia in patients with chronic kidney disease

2021 ◽  
Author(s):  
Fengqin Li ◽  
Hui Guo ◽  
Jianan Zou ◽  
Chensheng Fu ◽  
Song Liu ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Clinical Classification

scholarly journals 310 A new proposal for the clinical classification of vulvar lichen sclerosus: an observational prospective study

2020 ◽  
Author(s):  
Veronica Boero ◽  
Carlo A Liverani ◽  
Massimiliano Brambilla ◽  
Ermelinda Monti ◽  
Filippo Murina ◽  
...  
Keyword(s):  
Prospective Study ◽  
Lichen Sclerosus ◽  
Clinical Classification ◽  
Observational Prospective Study ◽  
Vulvar Lichen Sclerosus

scholarly journals Rationale for a clinical classification of lymphedema

2010 ◽  
Vol 10 (S1) ◽  
Author(s):  
V Gasbarro ◽  
S Michelini ◽  
E Tsolaki ◽  
M Ricci ◽  
C Allegra
Keyword(s):  
Clinical Classification

scholarly journals Clinical classification of cardiac deaths.

Circulation ◽  
1982 ◽  
Vol 65 (3) ◽  
pp. 457-464 ◽  
Author(s):  
L E Hinkle ◽  
H T Thaler
Keyword(s):  
Clinical Classification

scholarly journals The relationship between clinical classification of cataract and lens hardness

Eye ◽  
1993 ◽  
Vol 7 (6) ◽  
pp. 726-730 ◽  
Author(s):  
P Heyworth ◽  
G M Thompson ◽  
H Tabandeh ◽  
S McGuigan
Keyword(s):  
Clinical Classification ◽  
The Relationship

scholarly journals Classification of RA Into Active or Inactive With a Modified DAS, for Future Use as a Treat-to-target Tool, With a HandScan Score Replacing Joint Counts

2021 ◽  
Author(s):  
Maxime Verhoeven ◽  
Anton Westgeest ◽  
Janneke Tekstra ◽  
Jacob van Laar ◽  
Floris Lafeber ◽  
...  
Keyword(s):  
Medical Records ◽  
Roc Curves ◽  
Predictor Variables ◽  
Treat To Target ◽  
Reference Standard ◽  
Clinical Classification ◽  
Operating Characteristics ◽  
Clinical Interpretation ◽  
Activity Measures

Abstract ObjectivesTo establish the value of a modified DAS (DAS-OST) without joint counts but with a HandScan score (OST), versus that of DAS28, to classify RA as active versus inactive, with as reference standard the rheumatologist's clinical classification.MethodsRA patients with at least one HandScan and DAS28 measurement performed at the same visit were included. Data was extracted from medical records, as was the clinical interpretation as active or inactive RA by the rheumatologist. Logistic regression analyses were performed to calculate areas under the receiver operating characteristics (AU-ROC) curves. The clinical interpretation was used as reference standard in all analyses, and disease activity measures were used as predictor variables. The performance of predictor variables (AU-ROCs) was compared.ResultsData of 1505 unique RA patients were used for analyses. The highest AU-ROC of 0.88 (95%CI 0.85 – 0.90) was shown for DAS28; AU-ROC of DAS-OST was 0.78 (95%CI 0.75 – 0.81), difference 0.10, p<0.01.ConclusionsCompared to DAS28, DAS-OST classified RA statistically significantly less well as active versus inactive, when using the clinical classification as reference standard. However, a DAS-modification without joint scores might have a place in strategies limiting routine outpatients’ visits to the rheumatologist.

scholarly journals Klasifikasi Sel Darah Putih dan Sel Limfoblas Menggunakan Metode Multilayer Perceptron Backpropagation

2019 ◽  
Vol 9 (2) ◽  
pp. 173
Author(s):  
Apri Nur Liyantoko ◽  
Ika Candradewi ◽  
Agus Harjoko
Keyword(s):  
Blood Cell ◽  
White Blood Cell ◽  
Blood Cells ◽  
White Blood Cells ◽  
Back Propagation ◽  
Cell Types ◽  
Diagnostic Process ◽  
The Subject ◽  
Processing Techniques

 Leukemia is a type of cancer that is on white blood cell. This disease are characterized by abundance of abnormal white blood cell called lymphoblast in the bone marrow. Classification of blood cell types, calculation of the ratio of cell types and comparison with normal blood cells can be the subject of diagnosing this disease. The diagnostic process is carried out manually by hematologists through microscopic image. This method is likely to provide a subjective result and time-consuming.The application of digital image processing techniques and machine learning in the process of classifying white blood cells can provide more objective results. This research used thresholding method as segmentation and  multilayer method of back propagation perceptron with variations in the extraction of textural features, geometry, and colors. The results of segmentation testing in this study amounted to 68.70%. Whereas the classification test shows that the combination of feature extraction of GLCM features, geometry features, and color features gives the best results. This test produces an accuration value 91.43%, precision value of 50.63%, sensitivity 56.67%, F1Score 51.95%, and specitifity 94.16%.

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