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

Observational Learning01:12

Observational Learning

250
Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
250
Introduction to Learning01:18

Introduction to Learning

486
Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
486
Associative Learning01:27

Associative Learning

469
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
469
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

134
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
134
Cognitive Learning01:21

Cognitive Learning

459
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...
459
Neural Circuits01:25

Neural Circuits

1.3K
Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
1.3K

You might also read

Related Articles

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

Sort by
Same author

Insurance, Race, and Socioeconomic Disparities in Receipt of Surgical Treatment for Melanoma in the United States: A Systematic Review.

The Journal of surgical research·2026
Same author

Mind the Gap: Impact of New Labels on Public Perceptions and Calculated Risk of Adverse Outcomes after a Melanoma In Situ Diagnosis-A Secondary Analysis of an Online Randomized Experiment.

Medical decision making : an international journal of the Society for Medical Decision Making·2026
Same author

The Economics of Nicotinamide for Keratinocyte Carcinoma Prevention: What Does the Evidence (Not) Support?

JAMA dermatology·2026
Same author

Perspectives of United States dermatologists on melanoma screening and overdiagnosis: a qualitative study.

Skin health and disease·2026
Same author

Incubating artificial intelligence initiatives and careers in dermatology.

The Journal of investigative dermatology·2026
Same author

Fairness aware subset selection for advancing equity in skin cancer detection.

Journal of the American Medical Informatics Association : JAMIA·2026

Related Experiment Video

Updated: Jul 30, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.2K

Deep learning for Mpox: Advances, challenges, and opportunities.

Shannon Wongvibulsin1, Adewole S Adamson2

  • 1Division of Dermatology, David Geffen School of Medicine at the University of California, Los Angeles, CA, USA.

Med (New York, N.Y.)
|May 13, 2023
PubMed
Summary
This summary is machine-generated.

Researchers developed a deep learning algorithm to identify Mpox virus (MPXV) skin lesions. This AI tool aids in diagnosing infectious diseases, expanding beyond dermatology

More Related Videos

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

829
A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.5K

Related Experiment Videos

Last Updated: Jul 30, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.2K
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

829
A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.5K

Area of Science:

  • Artificial Intelligence in Medicine
  • Dermatology and Infectious Diseases
  • Computational Pathology

Background:

  • Deep learning shows promise for skin cancer diagnosis.
  • Applications for diagnosing infectious skin diseases are less explored.
  • Mpox virus (MPXV) presents diagnostic challenges through skin lesions.

Purpose of the Study:

  • To develop and evaluate a deep learning algorithm for classifying skin lesions associated with Mpox virus (MPXV) infections.
  • To assess the potential of AI in identifying infectious dermatological conditions.

Main Methods:

  • Development of a deep learning model trained on images of skin lesions.
  • Classification of lesions to differentiate MPXV-related presentations.
  • Utilized a dataset of clinical images for algorithm training and validation.

Main Results:

  • The deep learning algorithm demonstrated capability in classifying skin lesions from MPXV infections.
  • Successful identification of characteristic MPXV skin lesion patterns using AI.
  • The study highlights AI's potential in infectious disease diagnostics.

Conclusions:

  • Deep learning algorithms can be effectively applied to diagnose infectious skin diseases like Mpox.
  • AI offers a promising tool for rapid and accurate identification of MPXV lesions.
  • Further research can expand AI applications in infectious disease dermatology.