IMPROVING PREDICTION OF BLOOD CANCER USING LEUKEMIA MICROARRAY GENE DATA AND CHI2 FEATURES WITH WEIGHTED CONVOLUTIONAL NEURAL NETWORK

Improving prediction of blood cancer using leukemia microarray gene data and Chi2 features with weighted convolutional neural network

Abstract Blood cancer has emerged as a growing concern over the past decade, necessitating early diagnosis for timely and effective treatment.The present diagnostic Activity Equipment method, which involves a battery of tests and medical experts, is costly and time-consuming.For this reason, it is crucial to establish an automated diagnostic system

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European economic governance through fiscal rules

The European Union has been one of the most enthusiastic proponents of fiscal rules.Following the European sovereign leather headstall debt crisis, the EU did not embark on a wide-scale governance reform with the aim of creating a fiscal union; rather, it started to cement the original architecture that had been built upon fiscal rules.By applying

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Cluster-HGNN: Deep Local Features Clustering for Few-Shot Image Classification With Hybrid Graph Neural Networks

Graph neural networks (GNNs) have Activity Equipment shown great promise in few-shot learning, where they typically represent the entire feature of a sample as a node.However, this approach can overlook finer details within the sample, as GNNs usually measure the distance between nodes to determine overall differences, making them prone to backgrou

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