Interpretable learning algorithms enable pathogenic potential assessment and virulence-associated gene discovery of <i>Vibrio parahaemolyticus</i>. [PDF]
Liu Z, Li Z, Zhang J, Brown CT, Wang L.
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RINet: synthetic data training for indirect estimation of clinical reference distributions. [PDF]
LeBien J, Velev J, Roche-Lima A.
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Determinants and Dynamics of COVID-19 Vaccine Hesitancy in University Students: A Machine Learning Analysis. [PDF]
Torres DL, Butt ZA.
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Mapping Heterogeneity in Psychological Risk Among University Students Using Explainable Machine Learning. [PDF]
Liu P, Tang J, Wang H, Zhang D.
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Improving Skin Lesion Diagnosis: A Hybrid Approach Using Orthogonal Combination of Local Binary Pattern Features and Ensemble Learning for Diagnostic Accuracy. [PDF]
Rahmani N, Ebrahimnezhad H.
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Independent risk factors and predictive model for high hospitalization costs in children with Mycoplasma pneumoniae pneumonia. [PDF]
Wang X +10 more
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Deep structural clustering reveals hidden systematic biases in RNA sequencing data. [PDF]
Su Q +5 more
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A flexible class of latent variable models for the analysis of antibody response data. [PDF]
Giorgi E, Wallin J.
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Variational Deep Alliance: A Generative Auto-Encoding Approach to Longitudinal Data Analysis. [PDF]
Feng S, Xie W, Nie Y.
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Quantifying phage-host dynamics using droplet microfluidics. [PDF]
Givelet L +3 more
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