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

Band Theory02:35

Band Theory

17.1K
When two or more atoms come together to form a molecule, their atomic orbitals combine and molecular orbitals of distinct energies result. In a solid, there are a large number of atoms, and therefore a large number of atomic orbitals that may be combined into molecular orbitals. These groups of molecular orbitals are so closely placed together to form continuous regions of energies, known as the bands.
The energy difference between these bands is known as the band gap.
Conductor, Semiconductor,...
17.1K
Classification of Titrimetric Analysis Based on Reaction Types01:01

Classification of Titrimetric Analysis Based on Reaction Types

1.5K
Titrimetric analysis in solution chemistry involves measuring the volume of solutions and is often called volumetric analysis. The standard solution of known concentration in the burette is called the titrant, whereas the solution of unknown concentration in the flask is called the analyte, or titrand. Titrimetric analyses can be classified into four types based on the reactions between the titrant and analyte.
Titrations between an acid and a base lead to neutralization reactions that form...
1.5K
Machines01:19

Machines

563
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
A free-body diagram of the...
563
Energy Bands in Solids01:01

Energy Bands in Solids

1.9K
Isolated atoms have discrete energy levels that are well described by the Bohr model. And, it quantifies the energy of an electron in a hydrogen atom as En. Higher quantum numbers 'n' yield less negative, closer electron energy levels.
 Band Formation:
When atoms are brought close together, as in a solid, these discrete energy levels begin to split due to the overlap of electron orbitals from adjacent atoms. This split occurs because of the Pauli exclusion principle, which states...
1.9K
Machines: Problem Solving II01:30

Machines: Problem Solving II

652
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
652
Machines: Problem Solving I01:22

Machines: Problem Solving I

698
A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
698

You might also read

Related Articles

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

Sort by
Same author

Differential Functional Connectivity Between Silent Reading and Resting-State fMRI and Their Relationships With Reading Performance in Children With and Without Dyslexia.

International journal of developmental neuroscience : the official journal of the International Society for Developmental Neuroscience·2025
Same author

Assessment of alterations in regional homogeneity and amplitude of low-frequency fluctuations in children with dyslexia.

Turkish journal of medical sciences·2025
See all related articles

Related Experiment Video

Updated: Jan 24, 2026

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

447

Machine Learning-driven ADHD Classification: Exploring Medication Effects with VMD Sub-band Analysis.

Ebru Aker1, Şerife Gengeç Benli2, Zeynep Ak1

  • 1Department of Biomedical Engineering, Graduate School of Natural and Applied Sciences, Erciyes University, Kayseri, Turkey.

Current Computer-Aided Drug Design
|January 23, 2026
PubMed
Summary

This study uses Variational Mode Decomposition (VMD) on resting-state fMRI data to accurately classify Attention Deficit Hyperactivity Disorder (ADHD) subtypes and assess medication effects, offering an objective diagnostic tool.

Keywords:
ADHD classificationADHD subtypes.fMRI signal decompositionmachine learningmedication usagesub-bands

More Related Videos

Asthma Detection Research Based on Voice Signal Processing and Machine Learning
04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

951
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.9K

Related Experiment Videos

Last Updated: Jan 24, 2026

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

447
Asthma Detection Research Based on Voice Signal Processing and Machine Learning
04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

951
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.9K

Area of Science:

  • Neuroimaging
  • Computational Neuroscience
  • Medical Informatics

Background:

  • Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder.
  • Current ADHD diagnosis relies on subjective assessments, necessitating objective, data-driven methods.
  • Neuroimaging, particularly resting-state fMRI, offers potential for objective ADHD assessment.

Purpose of the Study:

  • To classify ADHD subtypes using resting-state fMRI data.
  • To evaluate the effects of medication on ADHD classification.
  • To develop an objective, computer-aided diagnostic approach for ADHD.

Main Methods:

  • Resting-state fMRI data from the ADHD-200 dataset were analyzed.
  • Functional MRI signals were converted to 1D and decomposed into sub-bands using Variational Mode Decomposition (VMD).
  • Statistical features were extracted and classified using Support Vector Machines (SVM), Linear Discriminant Analysis (LDA), and Artificial Neural Networks (ANN).

Main Results:

  • VMD-derived features significantly enhanced classification performance.
  • LDA achieved high accuracy: 96.34% (non-medicated ADHD vs. controls) and 88.41% (medicated ADHD vs. controls).
  • Classification accuracy for medicated vs. non-medicated ADHD was 79.63%, and 69.51% for ternary classification across all groups.

Conclusions:

  • The VMD-based approach effectively improves ADHD subtype classification and medication effect assessment.
  • This method shows promise as an objective tool for ADHD diagnosis and treatment planning.
  • The complexity of ADHD neuroimaging data presents challenges for multi-class classification accuracy.