Results 81 to 90 of about 14,282,599 (300)

Comparative Drug Response Profiling in Neuroblastoma Cell Lines and Patient‐Derived Tumor Organoids

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT High‐risk neuroblastoma remains a leading cause of pediatric cancer mortality, and improved preclinical models are needed to guide therapeutic developments. We screened seven high‐risk neuroblastoma cell lines and three patient‐derived tumor organoids with 528 compounds alongside bone marrow controls, and compared them with external datasets ...
Krzysztof Wierbiłowicz   +12 more
wiley   +1 more source

The comparison of k-means and k-medoids algorithms for clustering the spread of the covid-19 outbreak in Indonesia

open access: yesIlkom Jurnal Ilmiah, 2021
The coronavirus spreads quickly through human-to-human transmission via close contact and respiratory droplets such as coughing or sneezing. Various studies have been carried out to deal with Covid-19.
Wargijono Utomo
doaj   +1 more source

Balanced K-Means for Clustering [PDF]

open access: yes, 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

Impact of Radiation Therapy on Physical and Psychosocial Health of Adolescents and Young Adults: A Joint Report From the Children's Oncology Group AYA and Radiation Oncology Committees

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Rates of cancer among adolescents and young adults (AYA), age 15–39 years, are increasing. Consequently, radiation oncologists are treating more AYAs who have diagnoses spanning both pediatric and adult practices. Compared to pediatric and older adult patients, AYAs face a unique set of challenges.
Hesham Elhalawani   +7 more
wiley   +1 more source

Social Functioning Within the First Years After Pediatric Brain Tumor Diagnosis and the Relationship With Family Psychosocial Risk

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Survivors of pediatric brain tumors (PBTs) can experience long‐term social difficulties, impacting quality of life. Beyond medical and environmental factors, family psychosocial risk may play a role in social outcomes by shaping the caregiving environment and may provide intervention options.
Renske H. Houben   +4 more
wiley   +1 more source

Profiling Academic Library Patrons using K-means and X-means Clustering

open access: yesInternational Journal of Technology, 2019
Information technology is now used very often, especially by individuals born between 1982 and 2002 (the Millennial generation). The academic library, which from its beginnings has been a storehouse for information through collections, is becoming ...
Aisyah Larasati   +5 more
doaj   +1 more source

Online k-means Clustering

open access: yesCoRR, 2019
11 pages, 1 ...
Cohen-Addad, Vincent   +3 more
openaire   +4 more sources

Training results for dissolved oxygen content prediction using the SC-K-means-RBF model.

open access: yes, 2018
Training results for dissolved oxygen content prediction using the SC-K-means-RBF model.
Qianqian Cheng (4872292)   +4 more
core   +1 more source

Retrospective Analysis of Donor Lymphocyte Infusions in Pediatric Patients With Mixed Chimerism After Hematopoietic Stem Cell Transplantation

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Allogeneic hematopoietic stem cell transplantation (alloHSCT) is an essential therapy for several malignant and nonmalignant diseases, but relapse and graft loss remain the principal threats to its success. Routine monitoring of chimerism and minimal residual disease (MRD) enables early detection of imminent recurrence and guides ...
Carmen Junk   +10 more
wiley   +1 more source

A Geometric Approach to $k$-means

open access: yesCoRR, 2022
\kmeans clustering is a fundamental problem in many scientific and engineering domains. The optimization problem associated with \kmeans clustering is nonconvex, for which standard algorithms are only guaranteed to find a local optimum. Leveraging the hidden structure of local solutions, we propose a general algorithmic framework for escaping ...
Jiazhen Hong   +3 more
openaire   +3 more sources

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