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1.
Comput Biol Med ; 30(4): 171-89, 2000 Jul.
Article in English | MEDLINE | ID: mdl-10821937

ABSTRACT

An approach based on the modified Karhunen-Loéve expansion (MKLE) of constitutive and facultative skin colour data acquired by colorimeters in melanoma patients and healthy control subjects, was used to identify two colour features defining skin-colour-associated risk of melanoma. None of four common statistical classifiers trained on colour features were sufficiently accurate for allowing skin colour alone to be used for classification purposes, though a Bayesian quadratic classifier matched the transformed data well. This study supersedes the indeterminate character of most common clinical criteria based on qualitative factors and, irrespective of the results of classification, provides objective skin colour information for the prevention of melanoma.


Subject(s)
Melanoma/etiology , Pattern Recognition, Automated , Skin Neoplasms/etiology , Skin Pigmentation , Algorithms , Bayes Theorem , Case-Control Studies , Colorimetry , Diagnosis, Computer-Assisted , Discriminant Analysis , Humans , Image Processing, Computer-Assisted , Multivariate Analysis , Risk Factors
2.
Med Eng Phys ; 21(4): 235-40, 1999 May.
Article in English | MEDLINE | ID: mdl-10514041

ABSTRACT

Variable reduction is an important issue in biomechanics, because the definition of a non-redundant set of variables necessary for a complete description of a given motor act provides information about the motor strategy. A systematic tool for dealing with variable reduction problems is Principal Component Analysis. In this paper, as an example of an application of this technique, the set of Ground Reaction Forces (GRFs) provided by a six-component force plate, gained during standing up in a heterogeneous population of 82 normal individuals, was reduced to a set of fewer variables. Each subject was required to stand up from a chair five times at different, randomly self selected, speeds, obtaining a data set of 410 trials. Principal Components (PCs) of GRFs were computed for each trial. On average, over the ensemble of trials, first and second PCs (PC1 and PC2) explained together 90% of PCs. Inter- and intra-individual repeatability of the first two PCs was investigated by examining the correlation coefficient between PC waveforms obtained from the whole set of trials and within the set of trials performed by the same subject, respectively. While the PC1 exhibited repeatable patterns, the second one, although repeatable within the group of trials performed by the same subject, displayed marked inter-individual variability. Therefore, PC1 was related to intrinsic aspects of the motor task and PC2 to inter-subject features.


Subject(s)
Movement/physiology , Posture/physiology , Adult , Aged , Aged, 80 and over , Biomechanical Phenomena , Female , Humans , Male , Middle Aged , Reference Values , Statistics as Topic/methods
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