Results 91 to 100 of about 131,772 (305)
Application of Data Mining for Tuberculosis Disease Classification Using K-Nearest Neighbor
Jurnal SisfokomThis study aims to find out how much the application of the K-NN method and the accuracy value obtained by the K-NN method in clarifying data of Tuberculosis patients. This research focuses on improving public health and developing science to help people
Delima Sitanggang +4 more
doaj +1 more source
Bias in nearest-neighbor hazard estimation [PDF]
In nonparametric curve estimation, the smoothing parameter is critical for performance. In order to estimate the hazard rate, we compare nearest neighbor selectors that minimize the quadratic, the Kullback-Leibler, and the uniform loss.
Weißbach, Rafael, Dette, Holger
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To evaluate the efficacy and safety of ofatumumab in patients with myelin oligodendrocyte glycoprotein antibody–associated disease (MOGAD), and compare it with rituximab. Methods We conducted a single–center, observational study including 22 MOGAD patients treated with ofatumumab and 21 treated with rituximab.
Yuxin Fan +5 more
wiley +1 more source
Spherical k-Nearest Neighbors Interpolation
CoRR, 2019 Geospatial interpolation is a challenging task due to real world data often being sparse, heterogeneous and inconsistent. For that matter, this work presents SkNNI, a spherical interpolation algorithm capable of working with such challenging geospatial data.
openaire +2 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Introduction Glucagon‐like peptide‐1 receptor agonists (GLP‐1 RAs) have demonstrated significant weight‐reducing effects and may offer benefits in idiopathic intracranial hypertension (IIH); however, recent concerns about the risk of non‐arteritic anterior ischemic optic neuropathy (NAION) have emerged.
Faisal A. Al‐Harbi +9 more
wiley +1 more source
K nearest neighbor reinforced expectation maximization method
, 2011 K nearest neighbor and Bayesian methods are effective methods of machine learning. Expectation maximization is an effective Bayesian classifier. In this work a data elimination approach is proposed to improve data clustering. The proposed method is based
Mehmet Aci, Avci M., Aci M., Mutlu Avci
core +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective We aim to comprehensively analyze how regional tumor and edema characteristics are associated with clinical presentations and survival outcomes in a large cohort of glioblastoma patients. Methods Patients with IDH‐wildtype glioblastoma who received brain MRI from 2010 to 2023 were included.
Daniel J. Zhou +16 more
wiley +1 more source
Peripheral Neutrophil Activation and Extracellular Trap Formation in Amyotrophic Lateral Sclerosis
Annals of Clinical and Translational Neurology, EarlyView.Markers of neutrophil activation are increased in plasma during ALS, and markers of NET formation associate with ALS survival. ABSTRACT Objectives Peripheral neutrophil levels in amyotrophic lateral sclerosis (ALS) inversely correlate with survival, suggesting a role for neutrophils in disease progression.
Lillia A. Baird +9 more
wiley +1 more source
JuTISI (Jurnal Teknik Informatika dan Sistem Informasi), 2019 E-marketplace has gained popularity with the Indonesian society resulting in the increment of products offered. Consequently, customers require more effort to search for products. In this study, we classified products from several e-marketplaces.
Danny Sebastian
doaj +1 more source
Klasifikasi Teks dengan Menggunakan Improved K-Nearest Neighbor Algorithm [PDF]
, 2010 ABSTRAKSI: Klasifikasi merupakan proses mengelompokkan suatu data ke dalam kelompok data yang telah ditentukan berdasarkan tingkat kemiripannya. Klasifikasi ini pun dapat diterapkan dalam dokumen teks, dengan tujuan mempermudah penentuan seluruh dokumen ...
Gema Megantara
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