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

Introduction to Learning01:18

Introduction to Learning

1.2K
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...
1.2K
Machines01:19

Machines

578
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...
578
Machines: Problem Solving II01:30

Machines: Problem Solving II

670
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.
670
Machines: Problem Solving I01:22

Machines: Problem Solving I

716
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...
716
Avoidance Learning and Learned Helplessness01:14

Avoidance Learning and Learned Helplessness

2.6K
Avoidance learning and learned helplessness are critical concepts in understanding behavioral responses to negative stimuli.
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...
2.6K
Associative Learning01:27

Associative Learning

1.3K
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...
1.3K

You might also read

Related Articles

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

Sort by
Same author

Mesopic Illumination in Natural Environments: Implications for Myopia Research.

Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists)·2026
Same author

Combination of tissue-derived and shape-based parameters for subclinical keratoconus detection.

Biomedical optics express·2026
Same author

Corrected Percentile Curves to Track Myopisation-The Anyang Childhood Eye Study.

Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists)·2026
Same author

Role of toric intraocular lenses in the correction of keratoconic eyes with cataract.

Journal of cataract and refractive surgery·2026
Same author

Estimating the optical properties of corneal tissue from the OCT speckle.

Biomedical optics express·2026
Same author

The Relationship Between Corneal Stiffness Distribution and Tomography in Keratoconus Patients.

American journal of ophthalmology·2025
Same journal

Comparison of Corneal Endothelial and Anterior Segment Changes After Nd:YAG Laser Capsulotomy in Eyes with and without Pseudoexfoliation Syndrome.

Seminars in ophthalmology·2026
Same journal

Longitudinal Structural and Functional Trajectories Following Netarsudil Intensification or Surgical Escalation in Primary Open-Angle Glaucoma.

Seminars in ophthalmology·2026
Same journal

Maternal Diabetes Mellitus During Pregnancy as a Risk Factor for Congenital Nasolacrimal Duct Obstruction in the Offspring - a Large-Scale National Study.

Seminars in ophthalmology·2026
Same journal

Clinical Spectrum and Genetics of Ocular Manifestations in Muscle Eye Brain Disease: A Literature Review.

Seminars in ophthalmology·2026
Same journal

Port Delivery System Vs Monthly Ranibizumab in VEGF-Driven Macular Disease: A Systematic Review and Meta-Analysis.

Seminars in ophthalmology·2026
Same journal

Genome Wide Pleiotropic Analysis Reveals Shared Genetic Architecture and Pathological Basis Between Retinitis Pigmentosa and Relevant Ocular Comorbidities.

Seminars in ophthalmology·2026
See all related articles

Related Experiment Video

Updated: Feb 1, 2026

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

1.0K

Introduction to Machine Learning for Ophthalmologists.

Alejandra Consejo1,2,3,4, Tomasz Melcer3, Jos J Rozema1,2

  • 1Department of Ophthalmology, Antwerp University Hospital, Edegem, Belgium.

Seminars in Ophthalmology
|December 1, 2018
PubMed
Summary
This summary is machine-generated.

Machine Learning (ML) offers ophthalmologists objective tools for diagnosing eye conditions, grading severity, and predicting disease progression. This review covers ML applications and foundational knowledge for understanding its role in ocular sciences.

Keywords:
Automated diagnosisartificial intelligencemachine learningneural networksvision sciences

More Related Videos

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

2.5K
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

7.5K

Related Experiment Videos

Last Updated: Feb 1, 2026

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

1.0K
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

2.5K
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

7.5K

Area of Science:

  • Ophthalmology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Modern diagnostic and imaging technologies produce vast amounts of data, challenging clinical information extraction.
  • Machine Learning (ML) provides objective methods to aid clinical decision-making and diagnosis.

Purpose of the Study:

  • To review the latest Machine Learning achievements in ocular sciences.
  • To provide a comprehensive overview of ML processes and foundational knowledge for ophthalmologists.

Main Methods:

  • Review of current literature on Machine Learning applications in ophthalmology.
  • Explanation of technical terms and ML concepts relevant to ocular sciences.

Main Results:

  • Machine Learning is valuable for diagnosing eye conditions, grading pathology severity, and early disease detection.
  • ML can predict the future evolution of ocular diseases, enhancing clinical practice.

Conclusions:

  • Machine Learning techniques are increasingly vital in ophthalmology for advanced diagnostics and patient management.
  • Understanding ML fundamentals is crucial for leveraging its full potential in ocular sciences.