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

7.7K
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...
7.7K

You might also read

Related Articles

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

Sort by
Same author

Donor-Acceptor Organic Fluorophores Encapsulated in Polystyrene Nanoparticles as High-Brightness Reporters for Fluorescent Lateral Flow Immunoassay of C-Reactive Protein.

Journal of fluorescenceĀ·2026
Same author

DN203316, a novel PPARĪ“ agonist, suppresses ferroptotic signaling and fibrogenesis in metabolic dysfunction-associated steatohepatitis.

Experimental & molecular medicineĀ·2026
Same author

VPS26A retromer complex and SNX27 mediate stress-induced Golgi bypass of membrane proteins.

Nature communicationsĀ·2026
Same author

Association of Dietary Acid Load with Metabolic Syndrome-Related Parameters Following Eating Habit Modification in Korean Adults.

NutrientsĀ·2026
Same author

Comprehensive metabolomics and phytochemical analyses identified important metabolites involved in the antioxidant activity of four Swiss chard cultivars (<i>Beta vulgaris</i> L. var. cicla) with different leaf colours.

Food chemistry: XĀ·2026
Same author

Salmon Nasal Cartilage Proteoglycan Ameliorate Joint Pain and Cartilage Degradation by Regulating Catabolic and Anabolic Homeostasis in MIA-Induced Osteoarthritis.

NutrientsĀ·2026

Related Experiment Video

Updated: Aug 15, 2025

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.3K

Machine Learning for Online Automatic Prediction of Common Disease Attributes Using Never-Ending Image Learner.

E Rajesh1, Shajahan Basheer1, Rajesh Kumar Dhanaraj1

  • 1School of Computing Science and Engineering, Galgotias University, Greater Noida 203201, India.

Diagnostics (Basel, Switzerland)
|January 8, 2023
PubMed
Summary

Automatic online prediction (OAP) uses machine learning and a Never-Ending Image Learner to accurately predict disease attributes from images. This improves upon existing methods for online healthcare diagnostics.

Keywords:
Internet technologyNever-Ending Image Learnerautomatic online predictionmachine learningonline healthcare systemvirtual image sensing

More Related Videos

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

1.6K
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.9K

Related Experiment Videos

Last Updated: Aug 15, 2025

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.3K
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

1.6K
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.9K

Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Medical Informatics

Background:

  • Online healthcare systems are growing, but user-submitted health queries on forums lack reliability and accuracy.
  • Mild symptoms often deter individuals from seeking in-person medical consultations, leading to reliance on unverified online information.
  • Existing online health prediction methods face challenges with accuracy and user response.

Purpose of the Study:

  • To propose and evaluate an Automatic Online Prediction (OAP) system for disease attribute prediction.
  • To leverage machine learning, specifically the Never-Ending Image Learner, for enhanced online healthcare diagnostics.
  • To improve the accuracy and efficiency of predicting common disease attributes from limited image data.

Main Methods:

  • Developed an Automatic Online Prediction (OAP) system using a Never-Ending Image Learner (NEIL) with machine learning.
  • Employed a multi-access edge computing platform for machine-learning-assisted prediction from multiple images via multiple-instance learning.
  • Utilized M-theory for efficient real-time image prediction and isotropic positioning for image data storage.

Main Results:

  • The proposed OAP method demonstrated higher accuracy in predicting common disease attributes compared to existing approaches.
  • The system achieved improved operating efficiency through the machine learning of multiple images with isotropic positioning.
  • Performance metrics confirmed the superior accuracy and efficiency of the NEIL-based OAP system.

Conclusions:

  • The proposed machine learning-based Automatic Online Prediction system offers a more accurate and efficient solution for online disease attribute prediction.
  • The integration of Never-Ending Image Learner and isotropic positioning enhances the reliability of online healthcare diagnostics.
  • This approach addresses the limitations of traditional online health forums by providing dependable, AI-driven medical insights.