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

Inhaled Medications01:23

Inhaled Medications

764
Inhaled medications are crucial for managing chronic obstructive pulmonary disease (COPD) and asthma. They are essential for effective treatment and control, ensuring optimal respiratory health and well-being. Inhaled medication delivers drugs directly to the lungs, providing a rapid onset of action and reducing systemic side effects compared to oral or injectable medications. Three primary types of inhalation devices are used to administer these medications: nebulizers, metered-dose inhalers...
764
Avoidance Learning and Learned Helplessness01:14

Avoidance Learning and Learned Helplessness

2.5K
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...
2.5K
Heart Failure V: Medical Management01:30

Heart Failure V: Medical Management

227
Medical Management of Acute Decompensated Heart Failure (ADHF)The primary goals of therapy for patients hospitalized with acute decompensated heart failure (ADHF) include:Relieving symptomsOptimizing volume statusSupporting oxygenation and ventilationMaintaining cardiac output (CO) and end-organ perfusionIdentifying and addressing the cause of ADHFPreventing complicationsProviding patient education on factors precipitating HF exacerbationPlanning for dischargeOngoing monitoring and assessment...
227
Endocarditis III: Medical Management01:18

Endocarditis III: Medical Management

219
Infective endocarditis management involves a multifaceted approach encompassing infection prevention, lifestyle modifications, pharmacological therapy, and surgical management.Infection Prevention:Hand Hygiene: Thorough handwashing is crucial to prevent the spread of infection. Hand hygiene should be performed regularly, especially before and after using the restroom.Oral Hygiene: Good oral hygiene is essential. It includes brushing teeth immediately after waking up and before bed, flossing...
219
Myocarditis III: Medical Management01:14

Myocarditis III: Medical Management

185
Myocarditis: Comprehensive Medical ManagementMyocarditis, the heart muscle inflammation, requires a comprehensive medical management strategy that addresses the underlying cause, provides supportive care, manages symptoms, and reduces cardiac workload.Infections and Autoimmune CausesAdminister appropriate antimicrobial therapy when an infectious agent causes myocarditis. For instance, penicillin treats infections caused by Group A Streptococcus. In cases where autoimmune processes are...
185
Pericarditis III: Medical Management01:17

Pericarditis III: Medical Management

322
The primary objectives of managing pericarditis are to determine the underlying cause, provide effective therapy for treatment and symptom relief, and promptly detect signs and symptoms of cardiac tamponade. The following outlines the essential aspects of medical management for pericarditis:ObjectivesDetermine the Cause: Identifying the underlying cause of pericarditis is crucial for targeted treatment. Causes include viral infections, autoimmune diseases, post-cardiac injury syndrome, and...
322

You might also read

Related Articles

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

Sort by
Same author

Total lower lip and chin replantation following a trampoline accident: Rescue surgery with intensive leech therapy.

Journal of stomatology, oral and maxillofacial surgery·2026
Same author

Between unity and disparity: current treatment protocols for common orofacial clefts in European expert centres.

International journal of oral and maxillofacial surgery·2024
Same author

Innovative scientific illustration training for surgery residents in Paris.

Journal of stomatology, oral and maxillofacial surgery·2024
Same author

[Development and growth of the forehead].

Annales de chirurgie plastique et esthetique·2024
Same author

[Forehead shape in "Toulouse" artificial skull deformations].

Annales de chirurgie plastique et esthetique·2024
Same author

Linking brain-heart interactions to emotional arousal in immersive virtual reality.

Psychophysiology·2024

Related Experiment Video

Updated: Jan 22, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

3.4K

Deep learning in medical image analysis: A third eye for doctors.

A Fourcade1, R H Khonsari2

  • 1Service de Chirurgie Plastique, Maxillo-faciale et Stomatologie, Centre Hospitalier de Gonesse, Gonesse, France.

Journal of Stomatology, Oral and Maxillofacial Surgery
|June 30, 2019
PubMed
Summary

Deep learning algorithms, specifically convolutional neural networks (CNNs), show promise in enhancing medical image analysis for visual diagnosis. While not replacing doctors, CNNs can optimize tasks in fields like radiology and pathology.

Keywords:
Artificial intelligenceComputer visionDeep learningImage analysisNeural networkSystematic review

More Related Videos

Using Learning Outcome Measures to assess Doctoral Nursing Education
10:07

Using Learning Outcome Measures to assess Doctoral Nursing Education

Published on: June 21, 2010

19.4K
Deep Vascular Imaging in the Eye with Flow-Enhanced Ultrasound
07:29

Deep Vascular Imaging in the Eye with Flow-Enhanced Ultrasound

Published on: October 4, 2021

2.8K

Related Experiment Videos

Last Updated: Jan 22, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

3.4K
Using Learning Outcome Measures to assess Doctoral Nursing Education
10:07

Using Learning Outcome Measures to assess Doctoral Nursing Education

Published on: June 21, 2010

19.4K
Deep Vascular Imaging in the Eye with Flow-Enhanced Ultrasound
07:29

Deep Vascular Imaging in the Eye with Flow-Enhanced Ultrasound

Published on: October 4, 2021

2.8K

Area of Science:

  • Medical imaging analysis
  • Artificial intelligence in medicine
  • Deep learning applications

Background:

  • Artificial intelligence (AI) is rapidly advancing in medicine.
  • Deep learning algorithms, particularly Convolutional Neural Networks (CNNs), offer potential for automating medical image analysis.

Purpose of the Study:

  • To systematically review the literature on CNNs for medical image analysis.
  • To investigate if CNNs can improve visual diagnosis in medicine.

Main Methods:

  • Systematic review of articles published before May 2019 using CNNs for medical image analysis.
  • Screening based on image analysis approach, algorithm, dataset, training, testing, comparison, and results (accuracy, sensitivity, specificity).

Main Results:

  • 25 relevant papers (2013-2019) were identified from 352 initial articles.
  • CNNs, including AlexNet and GoogleNet, demonstrated applicability to medical images across various specialties.
  • Training CNNs required large datasets, often from international collaborations.

Conclusions:

  • CNNs can optimize routine medical tasks, positively impacting clinical practice.
  • Specialties like radiology and pathology are expected to be significantly transformed.
  • Medical practitioners play a crucial role in developing and implementing AI tools.