Results 61 to 70 of about 14,277,947 (281)
Ewing Sarcoma in Infants and Children Under 2 Years of Age: A French Retrospective Study
Pediatric Blood &Cancer, EarlyView.ABSTRACT Ewing sarcoma, the second most common primary bone cancer in children, requires intensive treatment that may lead to significant long‐term sequelae, particularly in infants. We retrospectively analyzed data from 1621 French patients treated between 1988 and 2015 within the EW88/93/97 or EE99 trials, focusing on 17 infants diagnosed before 24 ...
Elodie Verdier +18 more
wiley +1 more source
Efficient High-Dimensional Kernel k-Means++ with Random Projection
Applied Sciences, 2021 Using random projection, a method to speed up both kernel k-means and centroid initialization with k-means++ is proposed. We approximate the kernel matrix and distances in a lower-dimensional space Rd before the kernel k-means clustering motivated by ...
Jan Y. K. Chan, Alex Po Leung, Yunbo Xie
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Pediatric thromboembolism is increasingly encountered in critical care. Systemic thrombolysis with tissue plasminogen activator (tPA) facilitates vessel or valve patency, yet pediatric‐specific protocols remain undefined, and safety concerns persist. Objective To evaluate the efficacy and safety of a tailored, prolonged systemic tPA
Eran Shostak +5 more
wiley +1 more source
Color image segmentation using a spatial k-means clustering algorithm [PDF]
, 2006 This paper details the implementation of a new adaptive technique for color-texture segmentation that is a generalization of the standard K-Means algorithm. The standard K-Means algorithm produces accurate segmentation results only when applied to images
Ilea, Dana E., Whelan, Paul F.
core +2 more sources
New bounds for $k$-means and information $k$-means
, 2021 In this paper, we derive a new dimension-free non-asymptotic upper bound for the quadratic $k$-means excess risk related to the quantization of an i.i.d sample in a separable Hilbert space. We improve the bound of order $\mathcal{O} \bigl( k / \sqrt{n} \bigr)$ of Biau, Devroye and Lugosi, recovering the rate $\sqrt{k/n}$ that has already been proved by
Appert, Gautier, Catoni, Olivier
openaire +2 more sources
Global Efforts to Reduce Paediatric Cancer Care Disparities in Radiotherapy: A Decade Change
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background We present an update on the status, needs and challenges faced by paediatric imaging and radiotherapy (RT) programmes globally after a previous survey conducted by the International Atomic Energy Agency (IAEA) 10 years prior. Methods We developed and distributed a 121‐question survey to radiation oncologists, medical physicists and ...
Raymond B. Mailhot Vega +10 more
wiley +1 more source
BarekengPopulation data is an important piece of information that is useful for regional planning and development. Insight into the state of an area is more straightforward to observe if there are grouped sub-districts.
Denny Nurdiansyah +4 more
doaj +1 more source
Soil data clustering by using K-means and fuzzy K-means algorithm
Telfor Journal, 2016 A problem of soil clustering based on the chemical characteristics of soil, and proper visual representation of the obtained results, is analysed in the paper. To that aim, K-means and fuzzy K-means algorithms are adapted for soil data clustering.
E. Hot, V. Popović-Bugarin
doaj +1 more source
Balanced K-Means for Clustering [PDF]
, 2014 We present a k-means-based clustering algorithm, which optimizes mean square error, for given cluster sizes. A straightforward application is balanced clustering, where the sizes of each cluster are equal. In k-means assignment phase, the algorithm solves the assignment problem by Hungarian algorithm.
Malinen Mikko, Fränti Pasi
openaire +2 more sources