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Full-Text Articles in Statistics and Probability
Differentiation Of Human, Dog, And Cat Hair Fibers Using Dart Tofms And Machine Learning, Laura Ahumada, Erin R. Mcclure-Price, Chad Kwong, Edgard O. Espinoza, John Santerre
Differentiation Of Human, Dog, And Cat Hair Fibers Using Dart Tofms And Machine Learning, Laura Ahumada, Erin R. Mcclure-Price, Chad Kwong, Edgard O. Espinoza, John Santerre
SMU Data Science Review
Hair is found in over 90% of crime scenes and has long been analyzed as trace evidence. However, recent reviews of traditional hair fiber analysis techniques, primarily morphological examination, have cast doubt on its reliability. To address these concerns, this study employed machine learning algorithms, specifically Linear Discriminant Analysis (LDA) and Random Forest, on Direct Analysis in Real Time time-of-flight mass spectra collected from human, cat, and dog hair samples. The objective was to develop a chemistry- and statistics-based classification method for unbiased taxonomic identification of hair. The results of the study showed that LDA and Random Forest were highly …
Minimizing The Perceived Financial Burden Due To Cancer, Hassan Azhar, Zoheb Allam, Gino Varghese, Daniel W. Engels, Sajiny John
Minimizing The Perceived Financial Burden Due To Cancer, Hassan Azhar, Zoheb Allam, Gino Varghese, Daniel W. Engels, Sajiny John
SMU Data Science Review
In this paper, we present a regression model that predicts perceived financial burden that a cancer patient experiences in the treatment and management of the disease. Cancer patients do not fully understand the burden associated with the cost of cancer, and their lack of understanding can increase the difficulties associated with living with the disease, in particular coping with the cost. The relationship between demographic characteristics and financial burden were examined in order to better understand the characteristics of a cancer patient and their burden, while all subsets regression was used to determine the best predictors of financial burden. Age, …