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Items: 1 to 20 of 91

1.

Application of supervised self-organizing maps in breast cancer diagnosis by total synchronous fluorescence spectroscopy.

Dramićanin T, Dimitrijević B, Dramićanin MD.

Appl Spectrosc. 2011 Mar;65(3):293-7. doi: 10.1366/10-05928.

PMID:
21352649
2.

Principal component analysis and artificial neural network analysis of oral tissue fluorescence spectra: classification of normal premalignant and malignant pathological conditions.

Nayak GS, Kamath S, Pai KM, Sarkar A, Ray S, Kurien J, D'Almeida L, Krishnanand BR, Santhosh C, Kartha VB, Mahato KK.

Biopolymers. 2006 Jun 5;82(2):152-66.

PMID:
16470821
3.

Advanced integrated technique in breast cancer thermography.

Ng EY, Kee EC.

J Med Eng Technol. 2008 Mar-Apr;32(2):103-14.

PMID:
17852648
4.

Breast cancer diagnosis using self-organizing map for sonography.

Chen D, Chang RF, Huang YL.

Ultrasound Med Biol. 2000 Mar;26(3):405-11.

PMID:
10773370
5.

A rapid technique for classifying phytoplankton fluorescence spectra based on self-organizing maps.

Aymerich IF, Piera J, Soria-Frisch A, Cros L.

Appl Spectrosc. 2009 Jun;63(6):716-26. doi: 10.1366/000370209788559683.

PMID:
19531300
6.
7.

Neural network analysis of breast cancer from MRI findings.

Abdolmaleki P, Buadu LD, Murayama S, Murakami J, Hashiguchi N, Yabuuchi H, Masuda K.

Radiat Med. 1997 Sep-Oct;15(5):283-93.

PMID:
9445150
8.

Hybrid phosphorescence and fluorescence native spectroscopy for breast cancer detection.

Alimova A, Katz A, Sriramoju V, Budansky Y, Bykov AA, Zeylikovich R, Alfano RR.

J Biomed Opt. 2007 Jan-Feb;12(1):014004.

PMID:
17343479
9.

Identification of patients with congestive heart failure using different neural networks approaches.

Elfadil N, Hossen A.

Technol Health Care. 2009;17(4):305-21. doi: 10.3233/THC-2009-0542.

PMID:
19822947
10.

Support Vector Machine on fluorescence landscapes for breast cancer diagnostics.

Dramićanin T, Lenhardt L, Zeković I, Dramićanin MD.

J Fluoresc. 2012 Sep;22(5):1281-9. doi: 10.1007/s10895-012-1070-0. Epub 2012 Jun 8.

PMID:
22678149
11.

Autofluorescence and diffuse reflectance properties of malignant and benign breast tissues.

Breslin TM, Xu F, Palmer GM, Zhu C, Gilchrist KW, Ramanujam N.

Ann Surg Oncol. 2004 Jan;11(1):65-70.

PMID:
14699036
12.

Self-organizing map for cluster analysis of a breast cancer database.

Markey MK, Lo JY, Tourassi GD, Floyd CE Jr.

Artif Intell Med. 2003 Feb;27(2):113-27.

PMID:
12636975
13.

Classification of in vivo 1H MR spectra from breast tissue using artificial neural networks.

Bakken IJ, Axelson D, Kvistad KA, Gribbestad IS.

Anticancer Res. 2001 Mar-Apr;21(2B):1481-5. Erratum in: Anticancer Res 2001 Jan-Feb;21(1B):2861.

PMID:
11396236
14.

[Diagnostic application of serum protein pattern and artificial neural network software in breast cancer].

Hu Y, Zhang SZ, Yu JK, Liu J, Zheng S, Hu X.

Ai Zheng. 2005 Jan;24(1):67-71. Chinese.

PMID:
15642203
15.

Application of serum protein fingerprinting coupled with artificial neural network model in diagnosis of hepatocellular carcinoma.

Wang JX, Zhang B, Yu JK, Liu J, Yang MQ, Zheng S.

Chin Med J (Engl). 2005 Aug 5;118(15):1278-84.

PMID:
16117882
16.
17.

Comparison of multiexcitation fluorescence and diffuse reflectance spectroscopy for the diagnosis of breast cancer (March 2003).

Palmer GM, Zhu C, Breslin TM, Xu F, Gilchrist KW, Ramanujam N.

IEEE Trans Biomed Eng. 2003 Nov;50(11):1233-42.

PMID:
14619993
18.

A mixture of experts network structure for breast cancer diagnosis.

Ubeyli ED.

J Med Syst. 2005 Oct;29(5):569-79.

PMID:
16180491
19.

Prediction of breast cancer malignancy using an artificial neural network.

Floyd CE Jr, Lo JY, Yun AJ, Sullivan DC, Kornguth PJ.

Cancer. 1994 Dec 1;74(11):2944-8.

20.

Three-dimensional total synchronous luminescence spectroscopy criteria for discrimination between normal and malignant breast tissues.

Dramićanin T, Dramićanin MD, Jokanović V, Nikolić-Vukosavljević D, Dimitrijević B.

Photochem Photobiol. 2005 Nov-Dec;81(6):1554-8.

PMID:
16149859
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