Results 41 to 50 of about 1,170,104 (261)

A Bibliometric Analysis of Publications in Uremic Toxins From 1991 to 2024

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Uremic toxins are a growing area of research in nephrology, with significant implications in the progression and treatment of chronic kidney disease (CKD) and the management of end‐stage kidney disease (ESKD). This bibliometric analysis aims to evaluate the global research trends, key contributors, and the impact of publications in ...
Yuh‐Shan Ho, Karim M. Soliman, Wisit Cheungpasitporn, Wannasit Wathanavasin, Ahmed Daoud, Ahmed I. Kamal, Balázs Szamosfalvi, Tibor Fülöp   +7 more
wiley   +1 more source

Gaussian Processes for Missing Value Imputation

SSRN Electronic Journal, 2022
Missing values are common in many real-life datasets. However, most of the current machine learning methods can not handle missing values. This means that they should be imputed beforehand. Gaussian Processes (GPs) are non-parametric models with accurate uncertainty estimates that combined with sparse approximations and stochastic variational inference
Bahram Jafrasteh, Daniel Hernández-Lobato, Simón Pedro Lubián-López, Isabel Benavente-Fernández   +3 more
openaire   +4 more sources

On Gower Similarity Coefficient and Missing Values [PDF]

Annals of computer science and information systems, 2023
Marzena Kryszkiewicz
doaj   +1 more source

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

Therapeutic 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, Chimezie Okwuonu, Evelyn Idam, Folasade Adelekan‐Popoola, Shakirat Gold‐Olufadi, Olufunto Olufela Kalejaiye, Abdullateef Ogala, Zinnah Aloziem, Blossom Amamchukwu, Patience Elimia, Mkpoikanabasi Obot‐Obot, Henry Mbakwe, Praises Maduagwuna, Olatunji Akinrodoye, Chiamaka Anyanwu, Benjamin Anyanwu, Adedamola Akinsiku, Oluwatoyin A. Akinsiku, Muzamil O. Hassan, Fatiu A. Arogundade, Olalekan E. Ojo, Homayemem Weli, Jesupelumi Adenihun, Aderemi Adelaja, Ebun Bamgboye, Olalekan Olatise, Ade E. Faponle, Ayoola Odeyemi, Michael Muoka, Stephen Asaolu, Qudrat Busari, Blessing Dawudu, Michael Naiyeju, Rasheed A. Balogun   +33 more
wiley   +1 more source

Gap Filling and Quality Control Applied to Meteorological Variables Measured in the Northeast Region of Brazil

Atmosphere, 2021
In this work, we used the MICE (Multivariate Imputation by Chained Equations) technique to impute missing daily data from six meteorological variables (precipitation, temperature, relative humidity, atmospheric pressure, wind speed and insolation) from ...
Rafaela Lisboa Costa, Heliofábio Barros Gomes, David Duarte Cavalcante Pinto, Rodrigo Lins da Rocha Júnior, Fabrício Daniel dos Santos Silva, Helber Barros Gomes, Maria Cristina Lemos da Silva, Dirceu Luís Herdies   +7 more
doaj   +1 more source

Effectiveness of Resistance Intradialytic Exercise Compared to Aerobic Intradialytic Exercise for Patients With Chronic Kidney Disease: A Randomized Controlled Clinical Trial

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Patients with chronic kidney disease undergoing hemodialysis commonly experience reduced physical function, fatigue, poor sleep quality, and impaired health‐related quality of life. Intradialytic exercise has been proposed as a non‐pharmacological strategy to improve these outcomes.
Klebson da Silva Almeida, Gisela Cristiane Miyamoto, Daniel da Costa Torres, Ian Setubal Reis Chaves, Jonas do Carmo Paschoalin, Braúlio Lima Nascimento, Luciana Dias Chiavegato   +6 more
wiley   +1 more source

A Survey on Multivariate Time Series Imputation Using Adversarial Learning

IEEE Access
Multivariate time series (MTS) are captured in a great variety of real-world applications. However, analysing and modeling the data for classification and forecasting purposes can become very challenging if values are missing in the data set.
Anna Richter, Jyotirmaya Ijaradar, Ulf Wetzker, Vineeta Jain, Andreas Frotzscher   +4 more
doaj   +1 more source

Establishing an Apheresis Medicine Program in a Resource‐Constrained Setting: A 5‐Year Experience From Lagos, Nigeria

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Establishing a comprehensive apheresis medicine program in a resource‐constrained setting presents significant structural, financial, and logistical challenges. Despite the growing clinical importance of apheresis services globally, published experience from sub‐Saharan Africa remains sparse.
Folasade Adelekan‐Popoola, Shakirat Gold‐Olufadi, Olufunto Olufela Kalejaiye, Abdullateef Ogala, Rasheed A. Balogun   +4 more
wiley   +1 more source

Lookahead selective sampling for incomplete data

International Journal of Applied Mathematics and Computer Science, 2016
Missing values in data are common in real world applications. There are several methods that deal with this problem. In this paper we present lookahead selective sampling (LSS) algorithms for datasets with missing values.
Abdallah Loai, Shimshoni Ilan
doaj   +1 more source

Improving Load Forecasting of Electric Vehicle Charging Stations Through Missing Data Imputation

Energies, 2020
As the penetration of electric vehicles (EVs) accelerates according to eco-friendly policies, the impact of electric vehicle charging demand on a power distribution network is becoming significant for reliable power system operation.
Byungsung Lee, Haesung Lee, Hyun Ahn
doaj   +1 more source