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

You might also read

Related Articles

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

Sort by
Same author

[Advances of biological agents in the treatment of gastrointestinal acute graft-versus-host disease].

Zhonghua nei ke za zhi·2024
Same author

[Single hydrogen-methane breath test for the diagnosis of small intestinal bacterial growth].

Zhonghua nei ke za zhi·2023
Same author

[Research progress of obstructive sleep apnea syndrome on colorectal cancer].

Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases·2021
Same author

[New insight into the pathogenesis and treatment of juvenile polyposis syndrome].

Zhonghua er ke za zhi = Chinese journal of pediatrics·2020
Same author

[A survey on the current status and related factors of influenza vaccination among health care workers in tertiary hospitals of Xining city during the influenza epidemic season from 2017 to 2018].

Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine]·2019
Same author

[Analysis of project results of preventive medicine from the National Natural Science Foundation of China in 2017].

Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine]·2019
Same journal

The role of digital resources in surgical education: An analysis of YouTube videos on dynamic stabilization.

Technology and health care : official journal of the European Society for Engineering and Medicine·2026
Same journal

Behavioral patterns in iGaming across territories: Psychiatric and AI-driven insights via the internet of behavior.

Technology and health care : official journal of the European Society for Engineering and Medicine·2026
Same journal

Leveraging personal health records for early heart failure risk prediction through AI-driven modeling.

Technology and health care : official journal of the European Society for Engineering and Medicine·2026
Same journal

From data to prevention: A systematic review of artificial intelligence applications in sports injury prediction.

Technology and health care : official journal of the European Society for Engineering and Medicine·2026
Same journal

Leadership styles and work outcome in healthcare sector: Insights from bibliometric analysis.

Technology and health care : official journal of the European Society for Engineering and Medicine·2026
Same journal

Network analysis revealing research focus of the German Congress of Orthopedics and Trauma Surgery 2021.

Technology and health care : official journal of the European Society for Engineering and Medicine·2026
See all related articles

Related Experiment Video

Updated: Mar 20, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:33

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

1.4K

The research on medical image classification algorithm based on PLSA-BOW model.

C H Cao1,2,3, H L Cao1,2,3

  • 1College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, China.

Technology and Health Care : Official Journal of the European Society for Engineering and Medicine
|May 28, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces the Probabilistic Latent Semantic Analysis-Bag of Words (PLSA-BOW) model for enhanced medical image classification. The PLSA-BOW model improves accuracy by addressing issues with polysemous words and synonyms in medical imaging data.

Keywords:
Medical image classificationPLSAbag of words model

More Related Videos

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

43.8K
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

7.6K

Related Experiment Videos

Last Updated: Mar 20, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:33

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

1.4K
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

43.8K
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

7.6K

Area of Science:

  • Medical Imaging
  • Computer Science
  • Artificial Intelligence

Background:

  • Medical image classification is crucial for diagnosis and treatment.
  • Advancements in imaging technology necessitate improved classification methods.
  • Challenges exist with polysemous words and synonyms in medical image data.

Purpose of the Study:

  • To propose a novel model for accurate medical image classification.
  • To address limitations of existing classification methods, specifically polysemy and synonymy.
  • To enhance the performance of the bag-of-words model in the medical imaging domain.

Main Methods:

  • Adapted the bag-of-words model from text processing to the image domain.
  • Developed a visual bag-of-words model.
  • Integrated Probabilistic Latent Semantic Analysis (PLSA) with the bag-of-words model, creating the PLSA-BOW model.

Main Results:

  • The proposed PLSA-BOW model demonstrated improved classification accuracy.
  • The integration of PLSA effectively mitigated issues related to word ambiguity.
  • The visual bag-of-words approach proved beneficial for image classification tasks.

Conclusions:

  • The PLSA-BOW model offers a more accurate approach to medical image classification.
  • This method enhances the utility of bag-of-words techniques in medical imaging.
  • The findings support the use of PLSA-BOW for improved diagnostic and treatment support.