Results 51 to 60 of about 1,246,571 (292)
K-Means Algorithm to Identify the Elderly Psychological Stress Analysis Algorithm
Advances in Multimedia, 2022 In order to study the psychological anxiety of the elderly, a psychological stress recognition algorithm based on ECG signal acquisition and heart rate variability was proposed based on the K-means algorithm. By collecting ECG signals of the elderly, HRV
Yan Gao
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Making Roasted Mutton Colourimetric Card Based on Machine Vision Technology
Shipin gongye ke-ji, 2022 In order to establish a standardized method that can quickly and nondestructively identify the color changes in the process of mutton roasting, this study combined three algorithms (mean value algorithm, K-means algorithm and K-means+image noise ...
Bo WANG +3 more
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Journal of Engineering Research and Sciences: This is the extended version of a paper presented at CISP-BMEI 2023. After a general introduction kernels are described by showing how they arise from considerations concerning elementary geometrical properties.
Bernd Jürgen Falkowski
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background An earlier study on children diagnosed with acute lymphoblastic leukemia (ALL) at Moi Teaching and Referral Hospital (MTRH) in Kenya reported a low event‐free survival (EFS), excess treatment abandonment, and high induction mortality.
Gilbert Olbara +7 more
wiley +1 more source
An efficient approach based on differential evolution algorithm for data clustering [PDF]
Decision Science Letters, 2014 Clustering plays an essential role for data analysis and it has been widely used in different fields like data mining, machine learning and pattern recognition.
Maryam Hosseini +2 more
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Applied Sciences, 2022 Metaheuristic algorithms have been hybridized with the standard K-means to address the latter’s challenges in finding a solution to automatic clustering problems.
Abiodun M. Ikotun, Absalom E. Ezugwu
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Journal of Physics, Conference Series, 2019 K-Means is one of the most popular clustering algorithms because it is easy and simple when implemented. However, clustering results from K-Means are very sensitive to the selection of initial centroid.
Bernad Jumadi Dehotman Sitompul +2 more
semanticscholar +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT We report a retrospective single‐center analysis of pediatric patients with relapsed or refractory B‐cell precursor acute lymphoblastic leukemia focusing on relapses outside of the typical locations, bone marrow, central nervous system, or testes.
Johanna Kunz +7 more
wiley +1 more source
The K-Means Algorithm Evolution
Introduction to Data Science and Machine Learning, 2019 Clustering is one of the main methods for getting insight on the underlying nature and structure of data. The purpose of clustering is organizing a set of data into clusters, such that the elements in each cluster are similar and different from those in ...
J. Pérez-Ortega +5 more
semanticscholar +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Together, leukemia and lymphoma account for 38.7% of newly diagnosed pediatric cancer cases in the United States each year. Many caregivers utilize online resources to inform medical health decisions. Understanding the readability of these materials is critical to ensuring comprehensible patient education.
Chloe Strege +6 more
wiley +1 more source