Algorithm construction methodology for diagnostic classification of near-infrared spectroscopy data

Spectroscopy

Volumn 25, Issue 1, 2011, Pages 1-11

  Guevara, Ramón ^a,b,c   Stothers, Lynn ^a,b   MacNab, Andrew ^a,d  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^b UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^c BASQUE CENTER ON COGNITION   (Spain)

^d STELLENBOSCH UNIVERSITY   (South Africa)

Author keywords

Classification and regression tree (CART); diagnostic algorithm; linear discriminant analysis; near infrared spectroscopy; urodynamics

Indexed keywords

CART ANALYSIS; CHROMOPHORE CONCENTRATIONS; CLASSIFICATION ALGORITHM; CLASSIFICATION AND REGRESSION TREE; CLASSIFICATION AND REGRESSION TREE ANALYSIS; CLINICAL APPLICATION; CONSTRUCTION METHODOLOGY; DATA ANALYSIS; DATA EXAMPLES; DATA SETS; DIAGNOSTIC ALGORITHM; DIAGNOSTIC ALGORITHMS; FLOW STUDIES; LINEAR DISCRIMINANT ANALYSIS; MISCLASSIFICATION ERROR; MONITORING APPLICATIONS; NON-INVASIVE DIAGNOSTICS; OPTICAL TECHNIQUE; SAMPLE DATA; URODYNAMICS;

ALGORITHMS; CHROMOPHORES; DATA FLOW ANALYSIS; DISCRIMINANT ANALYSIS; DISEASES; HYDRODYNAMICS; INFRARED DEVICES; INFRARED SPECTROSCOPY; PATHOLOGY; REGRESSION ANALYSIS; SPECTRUM ANALYSIS; TEXTILES; TIME SERIES; UROLOGY;

TREES (MATHEMATICS);

ACCURACY; ARTICLE; BLADDER; BLADDER NECK STENOSIS; CHROMATOPHORE; CLASSIFICATION ALGORITHM; CLINICAL ARTICLE; CONCENTRATION (PARAMETERS); CONTROLLED STUDY; DIAGNOSTIC TEST; FLOW KINETICS; HUMAN; MALE; METHODOLOGY; MICTURITION; MUSCLE FUNCTION; NEAR INFRARED SPECTROSCOPY; NOMOGRAM; OPTICS; PELVIC ORGAN PROLAPSE; TIME SERIES ANALYSIS; URODYNAMICS;

EID: 79251475616     PISSN: 07124813     EISSN: None     Source Type: Journal    
DOI: 10.3233/SPE-2010-0486     Document Type: Article

References (35)

1. Y.N. Bhambhani, Muscle oxygenation trends during dynamic exercise measured by near infrared spectroscopy, Can. J. Appl. Physiol. 29 (2004), 504-523.
2. R. Boushel, R. Langberg, J. Olesen, J. Gonzales-Alonzo, J. Bulow and M. Kjaer, Monitoring tissue oxygen availability with near infrared spectroscopy (NIRS) in health and disease, Scand. J. Med. Sci. Sports 11 (2001), 213-222.
3. R. Boushel and C.A. Piantadosi, Near-infrared spectroscopy for monitoring muscle oxygenation, Acta Physiol. Scand. 168 (2000), 615-622.
4. L. Breiman, Classification and Regression Trees, Wadsworth International Group, Belmont, CA, USA, 1984, p. 358.
5. P. Comon, Independent component analysis: a new concept?, Signal Processing 36(3) (1994), 287-314.
6. R.O. Duda, P.E. Hart and D.G. Stork, Pattern Classification, Wiley, New York, 2001, p. 654.
7. M. Ferrari, L. Mottola and V. Quaresima, Principles, techniques, and limitations of near infrared spectroscopy, Can. J. Appl. Physiol. 29(4) (2004), 463-487.
8. A. Fielding, Cluster and Classification Techniquesfor the Biosciences, Cambridge Univ. Press, Cambridge, 2007, pp. 40-68.
9. G. Greisen, Is near-infrared spectroscopy living up to its promises?, Semin. Fetal. Neonatal. Med. 11(6) (2006), 498-502.
10. T. Hald, Pathophysiologyofthe Urinary Bladder in Obstruction and Ageing, Health Publications, London, 1988, pp. 131-138.
11. T. Hamaoka, K.K. McCully, V. Quaresima, K. Yamamoto and B. Chance, Near-infrared spectroscopy/imaging for mon-itoring muscle oxygenation and oxidative metabolism in healthy and diseased humans, J. Biomed. Opt. 12(6) (2007), 062105.
12. K.R. Hess, M.C. Abruzzese, R. Lenzi, M.N. Raber and J.L. Abruzzese, Classification and regression tree analysis of 1000 consecutive patients with unknown primary carcinoma, Clin. CancerRes. 5 (1999), 3403-3410.
13. A. Hyvärinen and E. Oja, Independent component analysis: algorithms and application, Neural Netw. 13(4,5) (2000), 411-430.
14. C.S. Lim and P. Abrams, The Abrams-Griffiths nomogram, WorldJ. Urol. 13 (1995), 34.
15. A.J. Macnab, Biomedical applications of near-infrared spectroscopy, in: Biological and Biomedical Spectroscopy, Ad-vances in Biomedical Spectroscopy, Vol. 2, A. Barth and P. Haris, eds, IOS Press, Amsterdam, 2009, pp. 355-402.
16. A.J. Macnab, B. Shadgan, L. Stothers and K. Afshar, Ambulant monitoring of bladder oxygenation and hemodynamics using wireless near-infrared spectroscopy, J. Can. Urol. Assoc (2011), in press.
17. AJ. Macnab and L. Stothers, Development of a near-infrared spectroscopy instrument for applications in urology, Can. J. Urol. 15(5) (2008), 4233-4240.
18. A.J. Macnab and L. Stothers, Near infrared spectroscopy: validation of bladder-outlet obstruction assessment using non-invasive parameters, Can. J. Urol. 15(5) (2008), 4241-4248.
19. J. Mair, J. Smidt, P. Lechleitner, F. Dienstl and B. Puschendorf, A decision tree for the early diagnosis of acute myocardial infarction in non-traumatic chest pain patients at hospital admission, Chest 108 (1995), 1502-1509.
20. RJ. Marshall, The use of classification and regression trees in clinical epidemiology, J. Clin. Epidemiol. 54 (2001), 603.
21. S.P. Miller, J. Weiss, A. Barnwell, D.M. Ferriero, B. Latal-Hajnal, A. Ferrer-Rogers, N. Newton, J.C. Partridge, D.V. Glid-den, D.B. Vigneron and A.J. Barkovich, Seizure-associated brain injury in term newborns with perinatal asphyxia, Neurology 58(4) (2002), 542-548.
22. V.W. Nitti, Pressure flow urodynamic studies: the gold standard for diagnosing bladder outlet obstruction, Rev. Urol. 7(Suppl. 6) (2005), S14.
23. J. Pannek, Editorial comment on: Classification of male lower urinary tract symptoms using mathematical modeling and a regression tree algorithm of noninvasive near-infrared spectroscopy parameters, Eur Urol. 57(2) (2010), 332-333.
24. C. Payer, B. Urlesberger, M. Pauger and W. Muller, Apnea associated with hypoxia in preterm infants: impact on cerebral blood volume, Brain Dev. 25(1) (2003), 25-31.
25. P. Rolfe, In vivo near-infrared spectroscopy, Annu. Rev. Biomed. Eng. 2 (2000), 715-754.
26. H. Sato, M. Kiguchi, A. Maki, Y Fuchino, A. Obata, T. Yoro and H. Koizumi, Within-subject reproducibility of near-infrared spectroscopy signals in sensorimotor activation after 6 months, J. Biomed. Opt. 11 (2006), 014021.
27. B. Shadgan, K. Afshar, L. Stothers and A.J. Macnab, Near-infrared spectroscopy of the bladder: a new technique for studying lower urinary tract function in health and disease, in: Photonic Therapeutics and Diagnostics, N. Kollias et al., eds, Proc SPIE, Vol. 7548, 2010, DOI: 10.1117/12.841066.
28. B. Shadgan, W.D. Reid, R. Gharakhanlou, L. Stothers and AJ. Macnab, Wireless near-infrared spectroscopy of skeletal muscle oxygenation and hemodynamics during exercise and ischemia, Spectroscopy 23(5) (2009), 233-241.
29. B. Shadgan, L. Stothers and A.J. Macnab, A transvaginal probe for near-infrared spectroscopic monitoring of the bladder detrusor muscle and urethral sphincter, Spectroscopy 22(6) (2008), 429-436.
30. M.G. Sowa, L. Leonardi, J.R. Payette, K.M. Cross, M. Gomez and J.S. Fish, Classification of burn injuries using near-infrared spectroscopy, J. Biomed. Opt. 11 (2006), 054002.
31. L. Stothers, R. Guevara and AJ. Macnab, Classification of male urinary tract symptoms using mathematical modeling and aregression tree algorithm of non invasive near infrared spectroscopy parameters, Eur. Urol. 57(2) (2010), 327-333.
32. L. Stothers, B. Shadgan and A.J. Macnab, Urologic applications of infrared spectroscopy (NIRS), Can. J. Urol. 15(6) (2008), 4399-4409.
33. M.C. van der Sluijs, N.M.J. Colier, R.J.F. Houston and B. Oesberg, A new and highly sensitive continuous wave near-infrared spectrophotometer with multiple detectors, Proc SPIE 3194 (1997), 63-72.
34. M. Wolf, M. Ferrari and V. Quaresima, Progress of near-infrared spectroscopy and topography for brain and muscle clinical applications, J. Biomed. Opt. 12(6) (2007), 062104.
35. AJ. Wolfberg and AJ. du Plessis, Near-infrared spectroscopy in the fetus and neonate, Clin. Perinatol. 33 (2006), 707-728.