Results 81 to 90 of about 14,276,290 (299)

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

Neuropsychological and Educational Outcomes in Shwachman–Diamond Syndrome—A Report From the North American Shwachman–Diamond Syndrome Registry

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Shwachman–Diamond syndrome (SDS) is a rare autosomal recessive ribosomopathy characterized by bone marrow failure and multisystem involvement, with emerging evidence of associated neurocognitive impairment. Methods We conducted a retrospective study of 240 individuals with biallelic Shwachman–Bodian–Diamond syndrome (SBDS) mutations
Jane Koo   +11 more
wiley   +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

A Situational Assessment of the Diagnostic Landscape and Organizational Readiness to Implement Next‐Generation Sequencing at Two Childhood Cancer Treatment Centers in Ghana

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Purpose Next‐generation sequencing (NGS) has emerged as a promising approach to improve diagnostic accuracy, but its feasibility in low‐ and middle‐income countries remains unknown. This study characterized the diagnostic landscape and assessed organizational readiness for NGS implementation at two childhood cancer treatment centers in Accra ...
Melissa Carvalho   +6 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

Beyond the Document: A Single‐Center Qualitative Study of Survivorship Care Plan Barriers and Opportunities Across Pediatric Oncology Stakeholders

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Survivorship care plans (SCPs) summarize cancer treatment and guide risk‐based follow‐up for cancer survivors, yet remain difficult to create, share, and use. Stakeholder perspectives are needed to inform usable approaches.
Molly S. Talman   +4 more
wiley   +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

Therapeutic Apheresis in Nigeria: A Multi‐Center Summary of Abstracts From the Inaugural Nigerian Society for Apheresis Scientific Meeting

open access: yesTherapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Therapeutic apheresis (TA) is an established treatment modality for hematologic, neurologic, and immunologic disorders, yet access remains severely limited in sub‐Saharan Africa. Donor apheresis, including platelet apheresis collection from healthy donors, represents an important complementary modality supporting blood product ...
Nosa Bazuaye   +33 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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