DEEP-LEARNING MODEL FOR INFLUENZA PREDICTION FROM MULTISOURCE HETEROGENEOUS DATA IN A MEGACITY: MODEL DEVELOPMENT AND EVALUATION

Deep-Learning Model for Influenza Prediction From Multisource Heterogeneous Data in a Megacity: Model Development and Evaluation

BackgroundIn megacities, there is an urgent need to establish more sensitive forecasting and early warning methods for acute respiratory infectious diseases.Existing prediction and early warning models for influenza and other acute respiratory infectious diseases have limitations and therefore there is room for improvement.ObjectiveThe aim of this

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cRegulome: an R package for accessing microRNA and transcription factor-gene expression correlations in cancer

Background Transcription factors and microRNAs play a critical role in regulating the gene expression in normal physiology and pathological conditions.Many bioinformatics tools were built to predict and identify transcription factor and microRNA targets and their role in Rooster the development of diseases including cancers.The availability of publ

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Improving Seismic Performance of RC Structures with Innovative TnT BRBs: A Shake Table and Finite Element Investigation

Addressing the critical seismic vulnerabilities of reinforced concrete (RC) beam-column joints remains an imperative research priority in earthquake engineering.This study presents an experimental Audio Transmitters and analytical investigation into the seismic performance enhancement of non-ductile RC frames using an innovative all-steel Tube-in-T

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