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posted on 2022-05-12, 17:28 authored by Eiron John Lugtu, Denise Bernadette Ramos, Alliah Jen Agpalza, Erika Antoinette Cabral, Rian Paolo Carandang, Jennica Elia Dee, Angelica Martinez, Julius Eleazar Jose, Abegail Santillan, Ruth Bangaoil, Pia Marie Albano, Rock Christian TomasFNN design architecture.
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support vector machinepositive predictive valuelung tumors (<lung cancer worldwidelung cancer basedclassical machine learningauxiliary diagnostic methodartificial neural network66 benign ).72 %, ppv30 %, npvinfrared spectral databenign samples baseddiv >< pcnn performed best36 %, accauc ), accuracy92 %, srsr ),09 %,infrared spectroscopybiopsy samples± 7± 3± 2± 12± 11± 1study aimedstratified 10relatively comparablerecall ratepotentially usedneeded alongsiden microscopic examinationincreasing prevalencefold crossdiscriminate malignantdeveloping fivecomputational tool93 %.56 malignant
