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Updated: Aug 29, 2025

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

Published on: May 10, 2024

Deep learning for Covid-19 forecasting: State-of-the-art review.

Firuz Kamalov¹, Khairan Rajab², Aswani Kumar Cherukuri³

¹Canadian University Dubai, United Arab Emirates.

|September 13, 2022

Summary

This summary is machine-generated.

This study surveys deep learning methods for Covid-19 forecasting, identifying 53 relevant papers. It categorizes models, analyzes performance, and suggests future research directions for improved forecasting.

Keywords:

CNN Covid-19 Deep learning Forecasting GNN LSTM MLP Survey

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Area of Science:

Epidemiology
Computer Science
Artificial Intelligence

Background:

The Covid-19 pandemic spurred the application of machine learning for crisis management.
A comprehensive survey of deep learning for Covid-19 forecasting was lacking.

Purpose of the Study:

To review and analyze existing deep learning methods for Covid-19 forecasting.
To categorize and evaluate the performance of identified deep learning models.
To identify limitations and suggest future research avenues.

Main Methods:

Systematic literature review of papers and preprints on Google Scholar (Apr 2020 - Feb 2022).
Inclusion criteria focused on deep learning approaches for Covid-19 forecasting.
Initial screening of 152 studies, with 53 selected for the survey.

Main Results:

A taxonomy of deep learning models for Covid-19 forecasting was developed.
Performance metrics of various models were described and analyzed.
Key deficiencies in current deep learning forecasting approaches were identified.

Conclusions:

The survey provides a consolidated overview of deep learning in Covid-19 forecasting.
Identified gaps highlight areas for methodological improvement.
This work serves as a resource for researchers in the field.