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

Behrens–Fisher Test00:57

Behrens–Fisher Test

278
The Behrens-Fisher test is a statistical method designed to address the Behrens-Fisher problem, which arises when comparing the means of two normally distributed populations with unequal variances. Unlike the Student's t-test, which assumes equal variances, the Behrens-Fisher test allows for mean comparison without this restrictive assumption. This flexibility makes it particularly valuable in scenarios where two independent samples exhibit normality but lack variance homogeneity.
This test...
278
Stereotypes, Prejudice, and Discrimination02:55

Stereotypes, Prejudice, and Discrimination

95.4K
Humans are very diverse and although we share many similarities, we also have many differences. The social groups we belong to help form our identities (Tajfel, 1974). These differences may be difficult for some people to reconcile, which may lead to prejudice toward people who are different. Prejudice is a negative attitude and feeling toward an individual based solely on one’s membership in a particular social group (Allport, 1954; Brown, 2010). Prejudice is common against people who...
95.4K
lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

10.0K
In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...
10.0K
Fisher's Exact Test01:08

Fisher's Exact Test

1.2K
Fisher's exact test is a statistical significance test widely used to analyze 2x2 contingency tables, particularly in situations where sample sizes are small. Unlike the chi-squared test, which approximates P-values and assumes minimum expected frequencies of at least five in each cell, Fisher's exact test calculates the exact probability (P-value) of observing the data or more extreme results under the null hypothesis. This feature makes it especially valuable when the assumptions of...
1.2K
Lattice Centering and Coordination Number02:33

Lattice Centering and Coordination Number

11.7K
The structure of a crystalline solid, whether a metal or not, is best described by considering its simplest repeating unit, which is referred to as its unit cell. The unit cell consists of lattice points that represent the locations of atoms or ions. The entire structure then consists of this unit cell repeating in three dimensions. The three different types of unit cells present in the cubic lattice are illustrated in Figure 1.
Types of Unit Cells
Imagine taking a large number of identical...
11.7K
Nursing Code of Ethics01:29

Nursing Code of Ethics

4.6K
The Nursing Code of Ethics sets the ethical benchmark for the profession, and guides nurses in ethical analysis and decision making at the societal, organizational, and clinical levels. The code encompasses showing compassion and respect for the patient, their families, and communities in all circumstances while committing to providing patient-centered care. In addition, the code states that nurses must advocate for the patient by defending a cause or recommendation to protect their rights,...
4.6K

You might also read

Related Articles

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

Sort by
Same author

HMGCR-Driven Cholesterol Metabolism Promotes Osteoarthritis Progression by Accelerating Synovial Fibroblast Senescence.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Cascade Nanozyme-Catalyzed Tophi Dissolution and ROS Scavenging for Anti-Inflammatory Therapy in Gouty Arthritis.

Small (Weinheim an der Bergstrasse, Germany)·2026
Same author

Influence of ZnO-Decorated Multi-Walled Carbon Nanotubes and Pure-Bore Biopolymers on Shale Chemical Stability and Fluid Loss Control.

ACS omega·2026
Same author

Erratum to: Distinct immune escape and microenvironment between RG-like and pri-OPC-like glioma revealed by single-cell RNA-seq analysis.

MedScience·2026
Same author

[Retracted] BAMBI inhibits inflammation through the activation of autophagy in experimental spinal cord injury.

International journal of molecular medicine·2026
Same author

S-palmitoylation regulates the function of the mitochondria-associated endoplasmic reticulum membrane to alleviate the senescence of nucleus pulposus cells.

PloS one·2026

Related Experiment Video

Updated: Feb 9, 2026

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques
09:48

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

Published on: June 30, 2017

7.9K

Fisher Discrimination Regularized Robust Coding Based on a Local Center for Tumor Classification.

Weibiao Li1, Bo Liao2, Wen Zhu1

  • 1College of Information Science and Engineering, Hunan University, Changsha, Hunan, 410082, China.

Scientific Reports
|June 16, 2018
PubMed
Summary

This study introduces Fisher discrimination regularized robust coding (FDRRC) for improved tumor classification. FDRRC enhances sparse representation models by incorporating dictionary learning, leading to superior cancer classification performance.

More Related Videos

Fully Human Tumor-based Matrix in Three-dimensional Spheroid Invasion Assay
08:15

Fully Human Tumor-based Matrix in Three-dimensional Spheroid Invasion Assay

Published on: May 7, 2019

16.3K
Assisted Selection of Biomarkers by Linear Discriminant Analysis Effect Size LEfSe in Microbiome Data
04:57

Assisted Selection of Biomarkers by Linear Discriminant Analysis Effect Size LEfSe in Microbiome Data

Published on: May 16, 2022

17.5K

Related Experiment Videos

Last Updated: Feb 9, 2026

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques
09:48

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

Published on: June 30, 2017

7.9K
Fully Human Tumor-based Matrix in Three-dimensional Spheroid Invasion Assay
08:15

Fully Human Tumor-based Matrix in Three-dimensional Spheroid Invasion Assay

Published on: May 7, 2019

16.3K
Assisted Selection of Biomarkers by Linear Discriminant Analysis Effect Size LEfSe in Microbiome Data
04:57

Assisted Selection of Biomarkers by Linear Discriminant Analysis Effect Size LEfSe in Microbiome Data

Published on: May 16, 2022

17.5K

Area of Science:

  • Computational biology
  • Medical informatics
  • Machine learning

Background:

  • Tumor classification is vital for cancer diagnosis and treatment.
  • Sparse representation-based classifiers (SRC) are used for tumor classification.
  • Existing SRC models have limitations in dictionary utilization and residual distribution assumptions.

Purpose of the Study:

  • To develop a novel and effective cancer classification technique.
  • To address the limitations of current sparse representation models in tumor classification.

Main Methods:

  • Proposed Fisher discrimination regularized robust coding (FDRRC) model.
  • Combined Fisher discrimination dictionary learning with regularized robust coding (RRC).
  • Assumed independent and identically distributed coding residual and representation coefficient for maximum a posteriori solution.

Main Results:

  • FDRRC demonstrated superior performance compared to state-of-the-art methods.
  • Extensive evaluation on various tumor datasets confirmed the model's effectiveness.
  • The proposed method showed improved accuracy in diverse classification tasks.

Conclusions:

  • FDRRC offers a significant advancement in tumor classification accuracy.
  • The integration of dictionary learning and robust coding enhances sparse representation models.
  • This novel technique holds promise for clinical cancer diagnosis and treatment.