Results 91 to 100 of about 18,390,026 (306)
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
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Introduction Adolescent siblings of children with cancer are at elevated risk for psychosocial problems. Unfortunately, various barriers such as limited family time and resources, conflicting schedules, and psychosocial staffing constraints at cancer centers hinder sibling access to support.
Christina M. Amaro +10 more
wiley +1 more source
Improved Guarantees for k-means++ and k-means++ Parallel
, 2020 In this paper, we study k-means++ and k-means++ parallel, the two most popular algorithms for the classic k-means clustering problem. We provide novel analyses and show improved approximation and bi-criteria approximation guarantees for k-means++ and k-means++ parallel.
Makarychev, Konstantin +2 more
openaire +2 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Hemoglobinopathies are prevalent globally; diagnosis is complex in high genetic admixture populations like Brazil. We report, in two pediatric siblings, the first documented cases in Brazil of heterozygosity for hemoglobin (Hb) O‐Arab with coinheritance of α‐thalassemia (αα/−α4.2; −α3.7/−α4.2), resulting in microcytic and hypochromic anemia ...
Elisângela de Souza Miranda Muynarsk +9 more
wiley +1 more source
Using classification and K-means methods to predict breast cancer recurrence in gene expression data
Journal of Medical Signals and Sensors, 2022 Background: Breast cancer is a type of cancer that starts in the breast tissue and affects about 10% of women at different stages of their lives.
Mohammadreza Sehhati +3 more
doaj +1 more source
, 2023 The k-means clustering algorithm (k-means for short) provides a method offinding structure in input examples. It is also called the Lloyd–Forgy algorithm as it was independently introduced by both Stuart Lloyd and Edward Forgy. k-means, like other algorithms you will study in this part of the book, is an unsupervised learning algorithm and, as such ...
openaire
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Neuropsychological complications may impair the qualitative prognosis of patients with pediatric brain tumors. However, multifaceted evaluations cannot be conducted in all patients because they are time consuming and burdensome for patients.
Ami Tabata +9 more
wiley +1 more source
Implementing Health‐Related Quality of Life Assessment in Pediatric Oncology: A Feasibility Study
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background There is growing interest in embedding health‐related quality of life (HRQoL) assessment and patient‐reported outcome measures (PROMs) within clinical cancer care. This study evaluated the feasibility, acceptability, and usability of implementing an electronic PROM (ePROM) platform to measure HRQoL in children with cancer ...
Mikaela Doig +13 more
wiley +1 more source
Treatment Decision‐Making Roles and Preferences Among Adolescents and Young Adults With Cancer
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Decision‐making (DM) dynamics between adolescents and young adults (AYAs) with cancer, parents, and oncologists remain underexplored in diverse populations. We examined cancer treatment DM preferences among an ethnically and socioeconomically diverse group of AYAs and their parents.
Amanda M. Gutierrez +14 more
wiley +1 more source