Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

269
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
269
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

644
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
644
Principles of Disease Surveillance01:26

Principles of Disease Surveillance

279
Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
279
Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

5.9K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
5.9K
Classification of Illness01:17

Classification of Illness

8.1K
The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
8.1K
Causality in Epidemiology01:21

Causality in Epidemiology

1.1K
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
1.1K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Hybrid deep ensemble architecture for robust diabetic retinopathy classification: leveraging transfer learning and CNN-transformer synergy.

Scientific reports·2026
Same author

Editorial: Smart dietary management for precision diabetes mellitus care.

Frontiers in nutrition·2026
Same author

Vision and convolutional transformers for Alzheimer's disease diagnosis: a systematic review of architectures, multimodal fusion and critical gaps.

Brain informatics·2025
Same author

4DfCF: 4D fMRI CrossFormer Vision Transformer.

IEEE journal of biomedical and health informatics·2025
Same author

Mortality prediction for ICU patients with mental disorders using large language models ensemble and unstructured medical notes.

PloS one·2025
Same author

Detecting malicious code variants using convolutional neural network (CNN) with transfer learning.

PeerJ. Computer science·2025

Related Experiment Video

Updated: Oct 30, 2025

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

1.3K

Comprehensive Survey of Using Machine Learning in the COVID-19 Pandemic.

Nora El-Rashidy1, Samir Abdelrazik2, Tamer Abuhmed3

  • 1Machine Learning and Information Retrieval Department, Faculty of Artificial Intelligence, Kafrelsheiksh University, Kafrelsheiksh 13518, Egypt.

Diagnostics (Basel, Switzerland)
|July 2, 2021
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) offers critical tools to combat coronavirus disease (COVID-19). This review surveys AI applications in diagnosis, spread estimation, vaccine development, and more, highlighting research challenges for future pandemic response.

Keywords:
COVID_19artificial intelligencedeep learning

More Related Videos

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections
06:22

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections

Published on: September 19, 2025

122
DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning
04:17

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

Published on: May 10, 2024

1.1K

Related Experiment Videos

Last Updated: Oct 30, 2025

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

1.3K
Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections
06:22

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections

Published on: September 19, 2025

122
DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning
04:17

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

Published on: May 10, 2024

1.1K

Area of Science:

  • Medical Informatics
  • Public Health
  • Artificial Intelligence

Background:

  • The COVID-19 pandemic, originating in December 2019, has placed a significant global health burden.
  • The World Health Organization declared COVID-19 an epidemic, straining healthcare systems worldwide.
  • Artificial intelligence (AI) presents a powerful technological solution to mitigate the pandemic's impact.

Purpose of the Study:

  • To survey the decisive role of artificial intelligence (AI) in combating the COVID-19 pandemic.
  • To identify and analyze key AI applications in the fight against COVID-19.
  • To compare existing COVID-19 datasets and highlight future research directions.

Main Methods:

  • Literature review of AI applications in COVID-19 research.
  • Categorization of AI's role into five significant areas.
  • Analysis of current COVID-19 datasets and identification of research gaps.

Main Results:

  • Five major AI applications for COVID-19 were identified: diagnosis, disease spread estimation, patient characteristic analysis, vaccine/drug development, and supporting tool creation.
  • AI aids in diagnosing COVID-19 using diverse data like images, sound, and text.
  • AI assists in predicting disease spread, understanding infection associations, and accelerating vaccine and drug development.

Conclusions:

  • AI plays a pivotal role in addressing the COVID-19 pandemic across multiple domains.
  • Further research into AI applications is crucial for enhancing future pandemic preparedness and response.
  • Addressing identified research challenges will unlock AI's full potential in public health crises.