Introduction Ensuring free access to essential medicines is a cornerstone of universal health coverage, yet many countries ...
In order to explore the medication rules of Shang Han Lun, this article conducted complex network analysis and cluster analysis on the 112 prescriptions in Shang Han Lun. Statistical and network ...
Introduction: In unsupervised learning, data clustering is essential. However, many current algorithms have issues like early convergence, inadequate local search capabilities, and trouble processing ...
In the field of affective computing (Muhl C. and G., 2014), automatic emotion recognition (AER) (Stern, 2002) has gained significant attention (Kim et al., 2013; Zhang et al., 2013), especially for ...
Missouri lawmakers have banned educators from leaning on a model of reading instruction called the “three-cueing” method as part of a bipartisan education package signed by Gov. Mike Kehoe on ...
Abstract: Clustering is an important unsupervised learning technique widely applied in data analysis and pattern recognition. Graph-based clustering methods have gained attention for their ability to ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Allosteric compounds offer an alternative mode of inhibition to orthosteric compounds ...
Abstract: This paper proposes a clustering method for crowdsourced test reports based on a large language model to solve the limitations of existing methods in processing repeated reports and ...
Cluster analysis can be used on symptom and behavior data to identify groups of similar individuals who may share underlying disease etiology or health risks. However, there are few clustering methods ...
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