Results 41 to 50 of about 1,444,731 (307)
Randomized Dimensionality Reduction for k-means Clustering [PDF]
, 2013 We study the topic of dimensionality reduction for $k$-means clustering. Dimensionality reduction encompasses the union of two approaches: \emph{feature selection} and \emph{feature extraction}.
Boutsidis, Christos +3 more
core
Evaluating the Genetic Overlap Between Congenital Heart Disease and Neuroblastoma Risk
Pediatric Blood &Cancer, EarlyView.ABSTRACT Children with congenital heart disease (CHD) have elevated neuroblastoma (NB) risk, potentially due to shared neural crest origins. We analyzed rare exonic de novo single‐nucleotide variants in 702 CHD and 454 NB trios from the Neuroblastoma Epidemiology in North America Study, Gabriella Miller Kids First Program, and a published cohort. Seven
Ji Yun Tark +7 more
wiley +1 more source
Color Feature Based Dominant Color Extraction
IEEE Access, 2022 The dominant colors in an image can be used for image search, color editing, palette generation, and several other applications. Conventionally, dominant colors are extracted using clustering or histogram-based methods.
Youngha Chang, Nobuhiko Mukai
doaj +1 more source
Extrema-weighted feature extraction for functional data
, 2017 Motivation: Although there is a rich literature on methods for assessing the impact of functional predictors, the focus has been on approaches for dimension reduction that can fail dramatically in certain applications.
Boom, Willem van den +3 more
core +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background In Ewing sarcoma (EwS), metastases, including those to bone marrow (BM), are the main factors influencing prognosis. Although reverse transcription polymerase chain reaction (RT‐PCR) offers greater sensitivity, the current EWING protocol defines BM metastases solely using light microscopic detection.
Thanh Pham +13 more
wiley +1 more source
Classification of EMI discharge sources using time–frequency features and multi-class support vector machine [PDF]
, 2018 This paper introduces the first application of feature extraction and machine learning to Electromagnetic Interference (EMI) signals for discharge sources classification in high voltage power generating plants.
Boreham, Philip +5 more
core +2 more sources
Clinical Correlates of Anxiety and Depression After Diagnosis of a Pediatric Brain Tumor
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background The prevalence and clinical correlates of symptoms of anxiety and depression in pediatric patients with brain tumors are not well described. We aimed to identify clinical characteristics that are correlated with elevated symptoms of anxiety and depression following initial diagnosis.
Bryony J. Lucas +16 more
wiley +1 more source
Modular Autoencoders for Ensemble Feature Extraction [PDF]
, 2015 We introduce the concept of a Modular Autoencoder (MAE), capable of learning a set of diverse but complementary representations from unlabelled data, that can later be used for supervised tasks.
Brown, Gavin, Reeve, Henry W J
core +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Anaplastic sarcoma of the kidney (ASK) is a DICER1‐associated malignant tumor presumed to arise in a benign precursor, pediatric cystic nephroma (PCN). However, the initial oncogenic alteration(s) associated with malignant transformation are unknown.
Nahir Cortes‐Santiago +6 more
wiley +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Ongoing evidence indicates increased risk of sarcopenic obesity among children and young people (CYP) with acute lymphoblastic leukemia (ALL), often beginning early in treatment, persisting into survivorship. This review evaluates current literature on body composition in CYP with ALL during and after treatment.
Lina A. Zahed +5 more
wiley +1 more source