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

Cognitive Learning01:21

Cognitive Learning

421
Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
421
Causality in Epidemiology01:21

Causality in Epidemiology

465
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
465
Hindsight Biases01:12

Hindsight Biases

3.4K
Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now? 
3.4K
Cause and Effect01:53

Cause and Effect

10.9K
While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable, is actually causing the systematic movement in our variables of interest. For instance, as sales in ice cream increase, so does the overall rate of crime. Is it possible that indulging in your favorite flavor of ice cream could send you on a crime spree? Or, after committing crime do you think you might decide to treat yourself to a cone?
10.9K
Introduction to Cognitive Psychology01:20

Introduction to Cognitive Psychology

525
Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem-solving, as well as other cognitive processes. Cognitive psychology studies how information is processed and manipulated in remembering, thinking, and knowing.
This field emerged in the mid-20th century, following a period dominated by behaviorism, which...
525
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

152
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
152

You might also read

Related Articles

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

Sort by
Same author

Postprandial Responses to Animal Products with Distinct Fatty Acid and Amino Acid Composition Are Diet-Dependent.

Nutrients·2025
Same author

Real-Time Predictive Condition Monitoring Using Multivariate Data.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2024
Same author

Corrigendum: Hyperspectral Video Analysis by Motion and Intensity Preprocessing and Subspace Autoencoding.

Frontiers in chemistry·2022
Same author

Hyperspectral Video Analysis by Motion and Intensity Preprocessing and Subspace Autoencoding.

Frontiers in chemistry·2022
Same author

Genome-wide association mapping for milk fat composition and fine mapping of a QTL for de novo synthesis of milk fatty acids on bovine chromosome 13.

Genetics, selection, evolution : GSE·2017
Same author

Frequency Analysis and Feature Reduction Method for Prediction of Cerebral Palsy in Young Infants.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2016
Same journal

Smartphone-assisted fluorescence and colorimetric dual-mode sensor for visual quantitative detection of nitrite and nitrate in real samples.

Analytica chimica acta·2026
Same journal

Folding integrated all-paper photoelectrochemical immunoassay using annealed ZnO for point-of-care detection of ferritin.

Analytica chimica acta·2026
Same journal

Dual-mode electrochemical-SERS detection of chloramphenicol based on dual-signal enhancement.

Analytica chimica acta·2026
Same journal

Multi-screening of beta-lactam antibiotics in milk based on Fe<sub>3</sub>O<sub>4</sub>@phage/bacteria system and aggregation induced emission luminogen.

Analytica chimica acta·2026
Same journal

A porous phosphate-rich β-cyclodextrin polymer for efficient and broad-spectrum enrichment of antibiotics.

Analytica chimica acta·2026
Same journal

Corrigendum to "LUMIN: A novel algorithm for automated mixture quantification using 1D <sup>1</sup>H NMR spectra" [Analytica Chimica Acta 1411 (2026) 345639].

Analytica chimica acta·2026
See all related articles

Related Experiment Video

Updated: Jul 18, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

277

Causality, machine learning and human insight.

Harald Martens1

  • 1Dept. Engineering Cybernetics, Norw. U. of Sci. & Technol. NTNU, Trondheim, Norway; Idletechs AS, Trondheim, Norway.

Analytica Chimica Acta
|August 21, 2023
PubMed
Summary
This summary is machine-generated.

Modern scientific instruments produce big data requiring information extraction. A new hybrid modeling framework converts this raw data into meaningful insights for future scientific applications.

More Related Videos

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
Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms
07:31

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms

Published on: February 8, 2019

6.6K

Related Experiment Videos

Last Updated: Jul 18, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

277
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
Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms
07:31

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms

Published on: February 8, 2019

6.6K

Area of Science:

  • Data Science
  • Scientific Computing
  • Information Science

Background:

  • Modern scientific instruments generate vast amounts of data (big data).
  • Effective utilization of this big data necessitates robust information extraction methods.
  • Current data handling approaches may not adequately address the scale and complexity of scientific big data.

Purpose of the Study:

  • To present a hybrid modeling framework for big data information extraction.
  • To convert raw, meaningless data into actionable, meaningful information.
  • To establish a foundation for future big data handling in science and technology.

Main Methods:

  • Development of a hybrid modeling framework.
  • Illustration of the framework's application.
  • Focus on information extraction techniques for big data.

Main Results:

  • Demonstration of a successful conversion of meaningless data to meaningful information.
  • Validation of the hybrid model's efficacy in data processing.
  • Establishment of a practical methodology for big data analysis.

Conclusions:

  • The hybrid modeling framework provides a viable solution for big data challenges in science.
  • Effective information extraction is crucial for leveraging big data.
  • The framework supports theoretical, practical, and democratic approaches to big data management.