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

The Representativeness Heuristic02:13

The Representativeness Heuristic

16.8K
The representative heuristic describes a biased way of thinking, in which you unintentionally stereotype someone or something. For example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.
16.8K
The Availability Heuristic01:08

The Availability Heuristic

7.1K
A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):
7.1K
Mechanism of Cardiac Arrhythmias01:28

Mechanism of Cardiac Arrhythmias

2.3K
Arrhythmias are irregular heart rhythms occurring when the heart's electrical impulses become abnormal. These disturbances can lead to various symptoms, depending on their severity and the underlying cause. Some common factors contributing to arrhythmias include hypoxia, ischemia, electrolyte imbalances, excessive catecholamine exposure, drug toxicity, and muscle overstretching. Arrhythmias can be classified into two main types based on the rate and site of origin of abnormal heart rhythms.
2.3K
Extraction: Advanced Methods00:56

Extraction: Advanced Methods

1.2K
Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
1.2K
The Anchoring-and-Adjustment Heuristic01:25

The Anchoring-and-Adjustment Heuristic

7.8K
In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. However, sometimes, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the...
7.8K
Heuristics01:21

Heuristics

756
Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
756

You might also read

Related Articles

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

Sort by
Same author

Transfusion-related adverse events in patients with restrictive or liberal transfusion strategy. An analysis of the MINT trial.

Transfusion·2025
Same author

Criminal emotion detection framework using convolutional neural network for public safety.

Scientific reports·2025
Same author

Basal reactive oxygen species determine the susceptibility to apoptosis in cirrhotic hepatocytes.

Free radical biology & medicine·2006
See all related articles

Related Experiment Video

Updated: Feb 16, 2026

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

2.7K

A meta-heuristic aided arrhythmia classification model using advanced deep learning technique with multiple feature

Jay Raval1, Kamalesh V N2, Dr Raj Kumar Patra3

  • 1Department of Computer Science and Engineering, Gandhinagar Institute of Technology, Gandhinagar University, Gujarat 382721, India.

Computational Biology and Chemistry
|February 14, 2026
PubMed
Summary

This study introduces an advanced deep learning model for accurate cardiac arrhythmia classification using Electrocardiogram (ECG) signals. The novel approach enhances diagnostic speed and precision by integrating multiple feature sets and optimizing the classification process.

Keywords:
Arrhythmia ClassificationAugmented Random value of Giant Armadillo OptimizationElectrocardiogram SignalsEnsemble Feature FusionOptimal Dense Recurrent neural network with Attention Mechanism

More Related Videos

Computer-Aided Three-Dimensional Visualization in the Treatment of Locally Advanced Thyroid Cancer
03:55

Computer-Aided Three-Dimensional Visualization in the Treatment of Locally Advanced Thyroid Cancer

Published on: June 9, 2023

1.1K
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

1.6K

Related Experiment Videos

Last Updated: Feb 16, 2026

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

2.7K
Computer-Aided Three-Dimensional Visualization in the Treatment of Locally Advanced Thyroid Cancer
03:55

Computer-Aided Three-Dimensional Visualization in the Treatment of Locally Advanced Thyroid Cancer

Published on: June 9, 2023

1.1K
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

1.6K

Area of Science:

  • Cardiology
  • Artificial Intelligence
  • Signal Processing

Background:

  • Cardiac arrhythmia is a life-threatening condition requiring accurate diagnosis.
  • Manual Electrocardiogram (ECG) interpretation is prone to inaccuracies.
  • Existing Artificial Intelligence (AI) models for arrhythmia detection face limitations in training time and manual feature selection.

Purpose of the Study:

  • To develop an intelligent deep learning model for precise cardiac arrhythmia classification.
  • To overcome the limitations of conventional AI models in training time and feature engineering.
  • To improve the accuracy and efficiency of irregular heartbeat identification.

Main Methods:

  • Utilized deep learning techniques including Conditional Autoencoder, Graph Convolutional Neural Network (GCNN), and Optimal Dense Recurrent neural network with Attention Mechanism (ODR-AM).
  • Extracted three distinct feature sets: deep features, wave features, and spectral features.
  • Employed an ensemble feature fusion strategy combined with Augmented Random value of Giant Armadillo Optimization (ARGAO) for parameter optimization.

Main Results:

  • The proposed model demonstrated enhanced performance in classifying specific types of cardiac arrhythmias.
  • The integration of diverse feature sets and advanced optimization techniques improved diagnostic accuracy.
  • Comparative analysis with conventional models indicated superior performance of the developed deep learning approach.

Conclusions:

  • The developed deep learning model offers a robust and efficient solution for cardiac arrhythmia classification.
  • This intelligent system has the potential to aid medical professionals in accurate and timely diagnosis of irregular heartbeats.
  • The study highlights the effectiveness of ensemble feature fusion and advanced optimization in improving AI-driven cardiovascular diagnostics.