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  • br In this work the SPA PAL v algorithm


    In this work, the SPA-PAL2v algorithm was applied to a complex database containing a greater Peroxynitrite of samples and arrangements than those of other works in the literature [3,9,10,13,19,20]. Com-parative results indicate that the PAL2v analysis technique, structured according to SPA-PAL2v, is very promising. One of its advantages is its computational structure, whereby the application of the paraconsistent algorithms allows the monitoring of the flow of information signals throughout the process, and several adjustments can be made to im-prove the analysis results. The SPA-PAL2v-based technique allows di-rect verification of the graphical results based on the number of simi-larity points between the study sample and the paraconsistent pattern. With comparisons focused on a specific Raman spectrum range, para-consistent analysis can be conducted using only the most significant parts of the spectrum, where more occurrences of similarities occur, to generate optimized paraconsistent patterns.
    6. Conclusions
    This work presents a set of interconnected and structured para-consistent algorithms to analyze the intensity values obtained by Raman spectroscopy stored in a database of ex vivo-extracted skin tissue samples. Special clusters of histopathological groups of samples ex-tracted from skin tissues were investigated through Raman spectro-scopy. The set of paraconsistent algorithms (SPA) was fully constructed by equations based on a type of PL that uses a two-valued annotation (PAL2v) and was therefore termed SPA-PAL2v. The PL belongs to the family of non-classical logics and accepts contradictions in its founda-tions without conflicts that invalidate the conclusions. Constructed through interpretations on a Hasse lattice, the formulation of the lo-gical-mathematical basis of the PAL2v algorithms adds unprecedented features to the SPA-PAL2v algorithm as a computational framework to treat Raman spectrum values in matrices and with possibilities of dif-ferent groups and configurations. This work presents relevant results, and the obtained percentage accuracies of some types of groupings surpassed those of the traditional methods of statistical analysis. The presented results validate the combination of PL-based techniques and the Raman data, thus opening up a broad field of research to support expert systems for medical diagnosis, especially when dealing with skin 
    cancer diseases using Raman spectral data.
    In future work, the SPA-PAL2v will be used to filter the database to extract evidence of the different techniques used for extracting the Raman intensity grades in various parts of the lesions and other types of groupings. This will result in an optimized computational structure to better characterize the possible diagnoses of skin cancer and other applications in different areas of human knowledge.
    The author Dorotéa Vilanova Garcia would like to acknowledge CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior) for the scholarship for the doctorate study in Biomedical Engineering. L. Silveira Jr. acknowledges FAPESP (São Paulo Research Foundation) for granting the Raman spectrometer (Process No. 2009/01788-5).
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