(Q62632520)

https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=EXT_ID:14504755%20AND%20SRC:MED&resulttype=core&format=json

19 December 2019

title

[An artificial neural network as a tool in risk evaluation of prostate cancer. Indication for biopsy with the PSA range of 2-20 microg/l] (English)

1 reference

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19 December 2019

9

1 reference

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19 December 2019

author name string

C Stephan

1

1 reference

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19 December 2019

B Vogel

2

1 reference

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19 December 2019

H Cammann

3

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19 December 2019

M Lein

4

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19 December 2019

V Klevecka

5

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19 December 2019

P Sinha

6

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19 December 2019

G Kristiansen

7

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19 December 2019

D Schnorr

8

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19 December 2019

S A Loening

10

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19 December 2019

publication date

22 March 2003

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19 December 2019

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19 December 2019

volume

42

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19 December 2019

issue

9

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19 December 2019

page(s)

1221-1229

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Prostate specific antigen: a decade of discovery--what we have learned and where we are going

19 December 2019

cites work

1 reference

12 December 2020

An artificial neural network considerably improves the diagnostic power of percent free prostate-specific antigen in prostate cancer diagnosis: results of a 5-year investigation.

1 reference

12 December 2020

Discordance of assay methods creates pitfalls for the interpretation of prostate-specific antigen values.

1 reference

12 December 2020

Use of percentage of free prostate-specific antigen to identify men at high risk of prostate cancer when PSA levels are 2.51 to 4 ng/mL and digital rectal examination is not suspicious for prostate cancer: an alternative model

1 reference

12 December 2020

Use of the percentage of free prostate-specific antigen to enhance differentiation of prostate cancer from benign prostatic disease: a prospective multicenter clinical trial

1 reference

12 December 2020

Receiver-operating characteristic as a tool for evaluating the diagnostic performance of prostate-specific antigen and its molecular forms--What has to be considered?

1 reference

12 December 2020

Novel artificial neural network for early detection of prostate cancer

1 reference

12 December 2020

Molecular forms of prostate-specific antigen in serum with concentrations of total prostate-specific antigen <4 microg/L: are they useful tools for early detection and screening of prostate cancer?

1 reference

12 December 2020

An algorithm combining age, total prostate-specific antigen (PSA), and percent free PSA to predict prostate cancer: results on 4298 cases.

1 reference

12 December 2020

Prostate-specific antigen, its molecular forms, and other kallikrein markers for detection of prostate cancer

1 reference

12 December 2020

Artificial Neural Networks in the Diagnosis and Prognosis of Prostate Cancer: A Pilot Study

1 reference

12 December 2020

Clinical implications of free-to-total immunoreactive prostate-specific antigen ratios

1 reference

12 December 2020

Predicting the outcome of prostate biopsy in screen-positive men by a multilayer perceptron network

1 reference

12 December 2020

Analytical performance and clinical validity of two free prostate-specific antigen assays compared

1 reference

12 December 2020

Percent free prostate-specific antigen for first-time prostate biopsy

1 reference

12 December 2020

Comparison of artificial neural networks with other statistical approaches: results from medical data sets

1 reference

12 December 2020

Performance of a neural network in detecting prostate cancer in the prostate-specific antigen reflex range of 2.5 to 4.0 ng/mL.

1 reference

12 December 2020

Estimation of prostate cancer probability by logistic regression: free and total prostate-specific antigen, digital rectal examination, and heredity are significant variables

1 reference

12 December 2020

10.1007/S00120-003-0322-7

Identifiers

DOI

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19 December 2019

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