Jove
Visualize
Contact Us

Related Concept Videos

Diagnosing Acidosis and Alkalosis01:24

Diagnosing Acidosis and Alkalosis

1.2K
Diagnosing acid-base imbalances involves systematically analyzing arterial blood samples, focusing on three key measurements: pH, bicarbonate (HCO3−) concentration, and carbon dioxide partial pressure (PCO2). This analysis follows a four-step process that helps identify the imbalance's underlying cause and nature.
First, the pH level is assessed to determine whether the blood pH is normal (7.35–7.45), low (acidosis), or high (alkalosis).
Next, the PCO2  and...
1.2K
Knee Joint01:23

Knee Joint

3.2K
The knee joint is the most complicated joint in the body. It consists of three articulations– two tibiofemoral and one patellofemoral. As is characteristic of synovial joints, the knee joint has a thin articular capsule that partially surrounds this joint cavity. Additionally, several ligaments, muscles, and cartilaginous structures support the movement of the knee.
A total of seven ligaments support the knee joint. The patellar ligament, which is also attached to the quadriceps femoris...
3.2K
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
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

18.7K
Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
18.7K
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
Purposive Learning01:22

Purposive Learning

508
E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...
508

You might also read

Related Articles

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

Sort by
Same author

Advancing Anemia Detection With Deep Neural Networks: A Comparative Analysis of Training Strategies Using Conjunctival Images.

American journal of hematology·2025
Same author

A Systematic Review on the Efficacy of Bisphosphonates on Osteogenesis Imperfecta.

Cureus·2025
Same author

Engineered Osteochondral Scaffolds with Bioactive Cartilage Zone for Enhanced Articular Cartilage Regeneration.

Annals of biomedical engineering·2024
Same author

The effect of socioeconomic status on clinical outcomes and implant survivorship after primary anatomic and reverse total shoulder arthroplasty.

Journal of shoulder and elbow surgery·2024
Same author

Impella 5.5: A Systematic Review of the Current Literature.

Innovations (Philadelphia, Pa.)·2024
Same author

Reversal of the Halo Effect: Prolonged Participation in Comprehensive Care for Joint Replacement Negatively Impacts Revision Metrics.

Arthroplasty today·2024
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 Experiment Video

Updated: Feb 4, 2026

Author Spotlight: Using a Rabbit Model to Explore the Efficacy of Tuina in Treating Knee Osteoarthritis
04:23

Author Spotlight: Using a Rabbit Model to Explore the Efficacy of Tuina in Treating Knee Osteoarthritis

Published on: August 25, 2023

2.1K

Comparing Real and ChatGPT-Generated Radiographs for Training Deep Learning Models to Diagnose Knee Osteoarthritis.

Rohan R Datir1, Akshay Reddy1, Yash Bhatia2

  • 1Medicine, California University of Science and Medicine, Colton, USA.

Cureus
|February 2, 2026
PubMed
Summary

Artificial intelligence (AI) models for osteoarthritis (OA) detection performed better with real radiographs than with ChatGPT-generated ones. Synthetic images can augment real data but not replace it for reliable OA diagnosis.

Keywords:
artificial intelligencedeep learningosteoarthritisradiograph analysissynthetic imaging

More Related Videos

Glycemic Impact on Knee Osteoarthritis Symptoms on Physical, Radiographic, and Inflammatory Markers among Individuals Aged 50 and Over with Diabetes
07:22

Glycemic Impact on Knee Osteoarthritis Symptoms on Physical, Radiographic, and Inflammatory Markers among Individuals Aged 50 and Over with Diabetes

Published on: March 7, 2025

1.0K
Author Spotlight: Investigating the Mechanism of Action of Acupotomy in Treating Knee Osteoarthritis
08:40

Author Spotlight: Investigating the Mechanism of Action of Acupotomy in Treating Knee Osteoarthritis

Published on: October 20, 2023

1.8K

Related Experiment Videos

Last Updated: Feb 4, 2026

Author Spotlight: Using a Rabbit Model to Explore the Efficacy of Tuina in Treating Knee Osteoarthritis
04:23

Author Spotlight: Using a Rabbit Model to Explore the Efficacy of Tuina in Treating Knee Osteoarthritis

Published on: August 25, 2023

2.1K
Glycemic Impact on Knee Osteoarthritis Symptoms on Physical, Radiographic, and Inflammatory Markers among Individuals Aged 50 and Over with Diabetes
07:22

Glycemic Impact on Knee Osteoarthritis Symptoms on Physical, Radiographic, and Inflammatory Markers among Individuals Aged 50 and Over with Diabetes

Published on: March 7, 2025

1.0K
Author Spotlight: Investigating the Mechanism of Action of Acupotomy in Treating Knee Osteoarthritis
08:40

Author Spotlight: Investigating the Mechanism of Action of Acupotomy in Treating Knee Osteoarthritis

Published on: October 20, 2023

1.8K

Area of Science:

  • Artificial intelligence in medical imaging
  • Radiographic diagnosis of osteoarthritis

Background:

  • Osteoarthritis (OA) is a degenerative joint disease with increasing global prevalence.
  • Automating radiographic diagnosis of OA is crucial due to its growing burden.
  • Artificial intelligence (AI) offers potential for automating OA diagnosis.

Purpose of the Study:

  • To compare AI models trained on real, synthetic (ChatGPT-generated), and combined radiographic datasets.
  • To evaluate the efficacy of synthetic imaging in improving OA detection.
  • To assess the role of synthetic data in augmenting diagnostic models.

Main Methods:

  • Trained three binary classifiers using knee radiographs: Model A (synthetic only), Model B (real only), and Model C (real + synthetic).
  • Evaluated models on 1,656 held-out real radiographs using metrics like accuracy, sensitivity, specificity, F1 score, and AUROC.
  • Employed McNemar's tests and bootstrap resampling for statistical comparisons.

Main Results:

  • Models trained on real data (B and C) outperformed the synthetic-only model (A).
  • Model C showed slightly improved discrimination (AUROC 0.782) compared to Model B (AUROC 0.758), with overlapping confidence intervals.
  • Synthetic data showed favorable but not statistically significant improvements in grade-specific sensitivity after adjustment.

Conclusions:

  • ChatGPT-generated radiographs alone are insufficient for training reliable OA diagnostic AI models.
  • Synthetic images can serve as a valuable adjunct to real radiographs for dataset expansion.
  • Synthetic imaging shows potential to enhance OA detection models but does not replace clinical imaging.