Background The global surge in ultra-processed food (UPF) consumption is a major public health challenge, particularly among ...
This issue proposes the creation of an extensive and well-organized examples gallery for the scikit-sampling library. Currently, the usage examples are limited. A comprehensive gallery will ...
This issue proposes adding cluster sampling capabilities to the scikit-sampling library. Cluster sampling is a probability sampling technique where the population is divided into naturally occurring ...
Objective: This study investigated the effect of communication about nutritional behavior changes on the nutritional knowledge and dietary practices of pregnant adolescents in the West Arsi Zone, ...
Abstract: Federated learning (FL) is an innovative privacy-preserving machine learning paradigm that enables clients to train a global model without sharing their local data. However, the coexistence ...
Abstract: Deep metric learning has gained significant attention recently due to its promising performance in image retrieval, face recognition, and clustering tasks. Deep metric learning algorithms ...
Helen Branswell covers issues broadly related to infectious diseases, including outbreaks, preparedness, research, and vaccine development. Follow her on Mastodon and Bluesky. You can reach Helen on ...
Background: Baseline mapping showed that schistosomiasis was highly/moderately endemic in nine districts in Sierra Leone. Mass drug administration (MDA) with praziquantel started in 2009, and after ...
Cluster sampling divides a population into smaller clusters, simplifying large-scale research. Cluster sampling is a probability sampling method where researchers divide a population into smaller ...
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