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

Regression Analysis01:11

Regression Analysis

8.1K
Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
8.1K
Regression Toward the Mean01:52

Regression Toward the Mean

6.9K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.9K
Microsoft Excel: Regression Analysis01:18

Microsoft Excel: Regression Analysis

1.5K
Regression analysis in Microsoft Excel is a powerful statistical method for examining the relationship between a dependent variable and one or more independent variables. It's used extensively in fields such as economics, biology, and business to predict outcomes, understand relationships, and make data-driven decisions. The most common type is linear regression, which attempts to fit a straight line through the data points to model the relationship between variables.
To perform regression...
1.5K
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
Multiple Regression01:25

Multiple Regression

3.8K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
3.8K
Autism Spectrum Disorder01:19

Autism Spectrum Disorder

1.0K
Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by persistent deficits in social communication and interaction alongside restrictive and repetitive behaviors or interests. ASD is sometimes accompanied by intellectual impairment.
These core symptoms manifest differently among individuals, ranging from mild to severe. The disorder's complexity extends beyond its clinical presentation, encompassing a diverse range of biological, cognitive, and sociocultural influences.
1.0K

You might also read

Related Articles

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

Sort by
Same author

RDoC-informed explainable AI as a paradigm for multilevel Alzheimer's disease diagnosis and progression prediction: a systematic review.

Brain informatics·2026
Same author

Autism Data Classification Using AI Algorithms with Rules: Focused Review.

Bioengineering (Basel, Switzerland)·2025
Same author

Assessing Autistic Traits in Toddlers Using a Data-Driven Approach with DSM-5 Mapping.

Bioengineering (Basel, Switzerland)·2023
Same author

Examining Cognitive Factors for Alzheimer's Disease Progression Using Computational Intelligence.

Healthcare (Basel, Switzerland)·2022
Same author

Autism screening: an unsupervised machine learning approach.

Health information science and systems·2022
Same author

A new classification system for autism based on machine learning of artificial intelligence.

Technology and health care : official journal of the European Society for Engineering and Medicine·2021
Same journal

AutoBiGluNet: transformer-based time series modeling for blood glucose prediction in Type 1 diabetes patients.

Health information science and systems·2026
Same journal

Multi-dimensional alignment framework with geometric intraoral constraints for precise occlusal registration.

Health information science and systems·2026
Same journal

SPSGL: uncovering psychiatric network mechanisms via structural-prior guided synaptic graph learning.

Health information science and systems·2026
Same journal

A noval 4D graph temporal brain network model for EEG-based depression detection.

Health information science and systems·2026
Same journal

PLETHSOMNet: automated identification of insomnia using deep neural network technique with photoplethysmography (PPG) signals.

Health information science and systems·2026
Same journal

Self-supervised fusion of clinical expertise and interpersonal skills for enhanced physician recommendation.

Health information science and systems·2026
See all related articles

Related Experiment Video

Updated: Jan 23, 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

A machine learning autism classification based on logistic regression analysis.

Fadi Thabtah1, Neda Abdelhamid2, David Peebles3

  • 11Digital Technologies, Manukau Institute of Technology, Auckland, New Zealand.

Health Information Science and Systems
|June 7, 2019
PubMed
Summary
This summary is machine-generated.

Early detection of Autistic Spectrum Disorder (ASD) is crucial. This study introduces a machine learning framework for efficient ASD screening in adults and adolescents, improving diagnostic accessibility.

Keywords:
Autism spectrum disorderClassificationClinical decision makingData miningFeature analysisMachine learningSensitivitySpecificity

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
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

2.4K

Related Experiment Videos

Last Updated: Jan 23, 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
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

2.4K

Area of Science:

  • Neurodevelopmental Disorders
  • Machine Learning Applications
  • Biomedical Data Analysis

Background:

  • Autistic Spectrum Disorder (ASD) presents significant healthcare costs, with early diagnosis offering potential cost reductions.
  • Effective and accessible screening methods are urgently needed due to the economic impact of autism.
  • Limited availability of non-genetic autism screening datasets hinders timely diagnosis.

Purpose of the Study:

  • To propose a novel machine learning framework for autism screening in adults and adolescents.
  • To identify influential features for autism screening through in-depth data analysis.
  • To develop a time-efficient screening tool to aid health professionals and individuals.

Main Methods:

  • Development of a machine learning framework for autism screening.
  • Utilizing logistic regression for predictive analysis on autism datasets.
  • Employing Information Gain (IG) and Chi-square (CHI) testing for feature analysis.

Main Results:

  • The machine learning framework demonstrated acceptable classification performance.
  • Key features influential in autism screening were identified.
  • The proposed methods provide valuable insights for autism screening.

Conclusions:

  • Machine learning offers a viable approach for developing effective autism screening tools.
  • Feature analysis is critical for optimizing screening tool performance.
  • This framework can enhance early identification and diagnosis of ASD.