A computational method called scSurv, developed by researchers at Institute of Science Tokyo, links individual cells to patient outcomes using widely available bulk RNA sequencing data. The approach ...
Latent spaces are abstract, high-dimensional areas within neural networks where patterns and relationships are encoded, but not readily interpretable by humans. Although latent space studies are still ...
Early identification and prediction of persistent SA-AKI are crucial. Objective: The aim of this study was to develop and validate an interpretable machine learning (ML) model that predicts persistent ...
Dr. Amy Baird, Professor of Biology at the University of Houston-Downtown (UHD), and her colleagues are seeking to change the attitude of biologists toward the meaning of taxonomic categories above ...
The ripeness level of bananas is a key factor for both producers and consumers, affecting the entire logistics chain of the fruit and its final price. Artificial intelligence techniques can be applied ...
Abstract: The classification of marine mammal calls is of enormous significance for the protection of marine mammals. Acoustic methods are the most effective tools for studying and monitoring marine ...
Abstract: Effective disaster prediction is essential for disaster management and mitigation. This study addresses a multi-classification problem and proposes the Neural-XGBoost disaster prediction ...
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