Deep Learning Methods, GNN Model, Community Service Work, China and USA, Neural Networks Share and Cite: Liu, J.X. (2026) A ...
Artificial intelligence is changing how we predict river flow—but a new study led by researchers at the University of British ...
Comparison of Deep-Learning Models for Classification of Cellular Phenotype From Flow Cytometry Data
Abstract: This study compares the relative utility of deep learning models as automated phenotypic classifiers, built with features of peripheral blood cell populations assayed with flow cytometry. We ...
Background Although chest X-rays (CXRs) are widely used, diagnosing mitral stenosis (MS) based solely on CXR findings remains ...
Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...
Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...
Since the inception of Next Gen Stats, we have relied on the basic logic of crediting a target in coverage to the closest defender to the receiver when the pass arrives. This method was directionally ...
This project demonstrates building a deep learning classification model using TensorFlow/Keras to predict whether an Initial Public Offering (IPO) will list at a profit or loss. The dataset contains ...
Introduction: The unmanned aerial vehicle -based light detection and ranging (UAV-LiDAR) can quickly acquire the three-dimensional information of large areas of vegetation, and has been widely used in ...
Background and objective: Accurate diagnosis of brain tumors significantly impacts patient prognosis and treatment planning. Traditional diagnostic methods primarily rely on clinicians’ subjective ...
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