MOISES OLIVEIRA DOS SANTOS
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Artigo IPEN-doc 28166 The impact of scan number and its preprocessing in micro-FTIR imaging when applying machine learning for breast cancer subtypes classification2021 - DEL-VALLE, MATHEUS; SANTOS, MOISES O. dos; SANTOS, SOFIA N. dos; CASTRO, PEDRO A.A. de; BERNARDES, EMERSON S.; ZEZELL, DENISE M.The breast cancer molecular subtype is an important classification to outline the prognostic. Gold-standard assessing using immunohistochemistry adds subjectivity due to interlaboratory and interobserver variations. In order to increase the diagnosis confidence, other techniques need to be examined, where the FTIR spectroscopy imaging allied with machine learning techniques may provide additional and quantitative information regarding the molecular composition. However, the impact of co-added scans acquisition parameter into machine learning classifications still needs better evaluation. In this study, FTIR images of Luminal B and HER2 subtypes were acquired varying the scan number and preprocessing techniques. It was demonstrated a spectral quality improvement when the scan number was increased, decreasing the standard deviation and outliers. Six machine learning models were used to classify the subtypes: Linear Discriminant Analysis, Partial Least Squares Discriminant Analysis, K-Nearest Neighbors, Support Vector Machine, Random Forest and Extreme Gradient Boosting. Best mean accuracy of 0.995 was achieved by Extreme Gradient Boosting model. It was found that all models achieved similar high accuracies with groups b256_064 (256 background and 064 scans), b256_128 and b128_128. Besides assessing the performance of different models, the b256_064 was established as the optimal group due to the minimum acquisition time. Therefore, this work indicates b256_064 for breast cancer subtype classification and also as a basis for other studies using machine learning for cancer evaluation.Artigo IPEN-doc 21297 Noninvasive monitoring of photodynamic therapy on skin neoplastic lesions using the optical attenuation coefficient measured by optical coherence tomography2015 - GOULART, VIVIANE P.; SANTOS, MOISES O. dos; LATRIVE, ANNE; FREITAS, ANDERSON Z.; CORREA, LUCIANA; ZEZELL, DENISE M.Photodynamic therapy (PDT) has become a promising alternative for treatment of skin lesions such as squamous cell carcinoma. We propose a method to monitor the effects of PDT in a noninvasive way by using the optical attenuation coefficient (OAC) calculated from optical coherence tomography (OCT) images. We conducted a study on mice with chemically induced neoplastic lesions and performed PDT on these lesions using homemade photosensitizers. The response of neoplastic lesions to therapy was monitored using, at the same time, macroscopic clinical visualization, histopathological analysis, OCT imaging, and OCT-based attenuation coefficient measurement. Results with all four modalities demonstrated a positive response to treatment. The attenuation coefficient was found to be 1.4 higher in skin lesions than in healthy tissue and it decreased after therapy. This study shows that the OAC is a potential tool to noninvasively assess the evolution of skin neoplastic lesions with time after treatment.Artigo IPEN-doc 18104 Effect of dental tissue conditioners and matrix metalloproteinase inhibitors on type I collagen microstructure analyzed by Fourier transform infrared spectroscopy2012 - BOTTA, SERGIO B.; ANA, PATRICIA A.; SANTOS, MOISES O.; ZEZELL, DENISE M.; MATOS, ADRIANA B.