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

Classification of Illness01:17

Classification of Illness

8.0K
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...
8.0K
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
Chronic Kidney Disease III: Interprofessional Care01:28

Chronic Kidney Disease III: Interprofessional Care

92
Chronic kidney disease (CKD) requires collaborative and comprehensive management. CKD progresses through stages and can lead to end-stage kidney disease (ESKD) if untreated. Interprofessional collaboration and patient education are crucial, enabling patients to manage their health and improve their quality of life.Diagnostic approach for chronic kidney diseaseThe diagnosis of CKD primarily focuses on the glomerular filtration rate (GFR), which assesses kidney function by measuring how well...
92
Chronic Pancreatitis II: Collaborative Care01:29

Chronic Pancreatitis II: Collaborative Care

133
The management of chronic pancreatitis is multifaceted, involving a comprehensive approach that includes thorough assessment, diagnostic testing, and a variety of management strategies.
Assessment:
133

You might also read

Related Articles

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

Sort by
Same author

PCOSFusion: a hybrid HOG-LBP feature-based approach for PCOS classification using StackPCOS and StackBoostPCOS.

Scientific reports·2026
Same author

Real-time yoga posture correction using deep learning for individuals with physical disabilities.

Scientific reports·2026
Same author

Knowledge enhanced framework for managing electricity generation and consumption in micro smart grids using Heronian mean MCDM approach.

Scientific reports·2026
Same author

Probiotic-Induced Gut Microbiota Modulation: A Comparative Analysis Using 16S rRNA V3-V4 and Targeted Sequencing.

Microorganisms·2026
Same author

Development of a Facemask System for Measuring Enteric Methane and Carbon Dioxide Production in Lactating Cows.

Animals : an open access journal from MDPI·2026
Same author

ATEdrug: A reliable human-in-the-loop annotation scheme for aspect term extraction and polarity detection in drug reviews.

PloS one·2026

Related Experiment Video

Updated: Sep 26, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

703

An Augmented Artificial Intelligence Approach for Chronic Diseases Prediction.

Junaid Rashid1, Saba Batool2, Jungeun Kim1

  • 1Department of Computer Science and Engineering, Kongju National University, Cheonan, South Korea.

Frontiers in Public Health
|April 18, 2022
PubMed
Summary

This study introduces an artificial intelligence (AI) approach using artificial neural networks (ANN) and particle swarm optimization (PSO) for early chronic disease diagnosis. The AI model achieved 99.67% accuracy, outperforming other methods for predicting conditions like cancer and diabetes.

Keywords:
artificial neural network (ANN)chronic diseasesfeature selectionmedical diagnosisprediction

More Related Videos

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform
07:13

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform

Published on: April 12, 2021

4.5K
Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.7K

Related Experiment Videos

Last Updated: Sep 26, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

703
Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform
07:13

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform

Published on: April 12, 2021

4.5K
Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.7K

Area of Science:

  • Artificial Intelligence
  • Machine Learning
  • Computational Biology

Background:

  • Chronic diseases represent a growing global health burden, increasing mortality rates worldwide.
  • Early diagnosis is crucial for improving patient survival and managing chronic conditions effectively.
  • Existing classification methods for disease prediction require further optimization for accuracy and efficiency.

Purpose of the Study:

  • To propose a novel augmented artificial intelligence approach for the early prediction of five prevalent chronic diseases.
  • To evaluate the performance of an artificial neural network (ANN) optimized with particle swarm optimization (PSO) against other classification algorithms.
  • To demonstrate the potential of the proposed model for enhancing chronic disease diagnosis in clinical settings.

Main Methods:

  • Development of an artificial neural network (ANN) model integrated with particle swarm optimization (PSO) for feature extraction and classification.
  • Comparison of the proposed ANN-PSO model against seven other classification algorithms, including random forest (RF), deep learning, and support vector machine (SVM).
  • Evaluation of model performance using accuracy metrics across various chronic disease datasets.

Main Results:

  • The proposed ANN-PSO model achieved a highest accuracy of 99.67% in predicting chronic diseases.
  • The ANN-PSO approach demonstrated superior performance compared to other state-of-the-art classification methods.
  • Optimized ANN processing exhibited reduced computation time compared to RF, deep learning, and SVM methods.

Conclusions:

  • The novel augmented AI approach using ANN with PSO significantly enhances the accuracy and efficiency of chronic disease prediction.
  • The model's performance is data-dependent, highlighting the importance of attribute selection in classification.
  • This approach holds promise for the development of advanced online diagnosis systems and early detection of chronic diseases in hospitals.