Emarene Mationg Kalaw

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We aimed to identify a prostate cancer DNA hypermethylation microarray signature (denoted as PHYMA) that differentiates prostate cancer from benign prostate hyperplasia (BPH), high from low-grade and lethal from non-lethal cancers. This is a non-randomized retrospective study in 111 local Asian men (87 prostate cancers and 24 BPH) treated from 1995 to 2009(More)
INTRODUCTION Nucleolar changes in cancer cells are one of the cytologic features important to the tumor pathologist in cancer assessments of tissue biopsies. However, inter-observer variability and the manual approach to this work hamper the accuracy of the assessment by pathologists. In this paper, we propose a computational method for prominent nucleoli(More)
We present an AdaBoost-based Ensemble Learning for supporting automated Gleason grading of prostate adenocarcinoma (PRCA). The method is able to differentiate Gleason patterns 4–5 from patterns 1–3 as the patterns 4–5 are correlated to more aggressive disease while patterns 1–3 tend to reflect more favorable patient outcome. This(More)
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