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

Lung Capacity01:47

Lung Capacity

56.3K
The air in the lungs is measured in volumes and capacities. Lung volume measures reflect the amount of air taken in, released, or left over after a lung function, like a single inhalation. Lung capacity measures are sums of two or more lung volume measures.
56.3K
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
Stages of Infection01:26

Stages of Infection

65.2K
Stages of infection describe what happens to a susceptible host once a pathogen invades the human body. The stages of infection are incubation, prodromal, illness, stage of decline, and convalescence. The incubation stage is the period from exposure to a pathogen until symptoms start. The infected person is unaware of impending illness as the pathogens grow and multiply within the body. The duration may vary depending on the type of infection. The incubation period of measles averages ten to...
65.2K
Stages of General Anesthesia01:22

Stages of General Anesthesia

1.7K
Various sedation levels offer significant advantages in facilitating procedural interventions for patients undergoing medical or invasive surgical procedures. These levels span from anxiolysis to general anesthesia, providing a spectrum of sedative effects to cater to specific patient needs. Anxiolysis reduces anxiety and is achieved through minimal sedation, enabling patients to remain awake and responsive while feeling more at ease during the procedure. This level can benefit minor...
1.7K
Stages of Sleep01:22

Stages of Sleep

1.4K
Sleep progresses through distinct stages, each characterized by specific brain wave patterns and physiological responses ranging from wakefulness to stages of non-rapid eye movement, known as non-REM, to rapid eye movement, referred to as REM. Understanding these stages helps in recognizing how sleep supports various bodily and cognitive functions.
Before sleep begins, in wakefulness, the brain exhibits primarily beta waves, which are high in frequency and low in amplitude, indicating alertness...
1.4K
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

GLP-1 Agonists Are Associated With a Significant Reduction in Breast Cancer Incidence in Women.

JCO oncology practice·2026
Same author

Large-Scale Teleradiology and Evolving Virtual Imaging Service in South Korea.

Telemedicine journal and e-health : the official journal of the American Telemedicine Association·2025
Same author

Characteristics and Outcomes of Patients Requiring Repeat Intensive Care Unit Consults.

Mayo Clinic proceedings. Innovations, quality & outcomes·2023
Same author

A blockchain-enabled sharing platform for personal health records.

Heliyon·2023
Same author

Patients Who Decompensate and Trigger Rapid Response Immediately Upon Hospital Admission Have Higher Mortality Than Equivalent Patients Without Rapid Responses.

Journal of patient safety·2023
Same author

Automated Error Labeling in Radiation Oncology via Statistical Natural Language Processing.

Diagnostics (Basel, Switzerland)·2023

Related Experiment Video

Updated: Feb 2, 2026

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer
07:53

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer

Published on: October 13, 2023

2.1K

Deep Learning Model With Nodule Indexing Tailored to Early-Stage Lung Cancer Detection.

Jamie L Schroeder1, Mary G Cormier2, ShihChung B Lo3

  • 1Radiology Department, Georgetown University Medical Center, Washington, District of Columbia.

Journal of the American College of Radiology : JACR
|January 31, 2026
PubMed
Summary

A deep learning artificial intelligence (AI) system significantly improved radiologist performance in detecting pulmonary nodules on CT scans. The AI tool enhanced cancer detection rates and reduced interpretation time, supporting its clinical integration.

Keywords:
Chest CT screeningartificial intelligenceearly-stage lung cancerpulmonary nodulesreader performance

More Related Videos

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

2.3K
Detection of Targetable Alterations in Non-small Cell Lung Cancer using Next-generation Sequencing
05:17

Detection of Targetable Alterations in Non-small Cell Lung Cancer using Next-generation Sequencing

Published on: October 10, 2025

415

Related Experiment Videos

Last Updated: Feb 2, 2026

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer
07:53

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer

Published on: October 13, 2023

2.1K
A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

2.3K
Detection of Targetable Alterations in Non-small Cell Lung Cancer using Next-generation Sequencing
05:17

Detection of Targetable Alterations in Non-small Cell Lung Cancer using Next-generation Sequencing

Published on: October 10, 2025

415

Area of Science:

  • Radiology
  • Artificial Intelligence
  • Medical Imaging

Background:

  • Pulmonary nodule detection on CT scans is crucial for early lung cancer diagnosis.
  • Subtle and early-stage lung cancers present diagnostic challenges for radiologists.
  • Deep learning-based AI systems offer potential for improving diagnostic accuracy.

Purpose of the Study:

  • To evaluate the impact of a deep learning AI system on radiologist performance in detecting pulmonary nodules.
  • To assess the AI system's ability to improve malignancy risk stratification and nodule indexing.
  • To validate AI performance on a dataset enriched with challenging early-stage lung cancers.

Main Methods:

  • A two-arm crossover reader study involving 16 board-certified radiologists interpreting 340 CT scans.
  • Radiologists interpreted scans with and without AI assistance, with a one-month washout period.
  • Localization-specific ROC (LROC) analysis was employed to evaluate performance on a dataset including screening and non-screening cases.

Main Results:

  • AI assistance significantly improved radiologists' LROC AUC for cancer detection (0.761 vs. 0.652) and all nodules (0.830 vs. 0.734).
  • Mean sensitivity increased from 0.585 to 0.727 with AI, while specificity remained stable.
  • Interpretation time decreased by 12.9% (mean 133 to 115.9 seconds) with AI assistance.

Conclusions:

  • The deep learning AI system substantially enhanced radiologist performance in pulmonary nodule detection.
  • The AI system demonstrated consistent benefits across various nodule types and screening contexts.
  • Integration of this AI system into routine chest CT interpretation workflows is supported.