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

Clinical Trials: Overview01:11

Clinical Trials: Overview

4.5K
Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...
4.5K
Drug Elimination: The Concept of Clearance01:06

Drug Elimination: The Concept of Clearance

3.7K
Drug elimination refers to removing drugs from the body, either through urine by the kidneys or through bile by the liver. Drug clearance is a pharmacokinetic parameter that measures the efficiency of drug removal from the bloodstream within a specific time frame. It is calculated as the rate at which a drug is eliminated from plasma divided by the plasma concentration of the drug.
Drug clearance is not limited to renal excretion but encompasses all organs involved in drug elimination,...
3.7K
Clinical Trials01:16

Clinical Trials

10.1K
Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
10.1K
Drug Elimination: Overview01:18

Drug Elimination: Overview

2.4K
Drug elimination involves many complex processes and does not necessarily differentiate between distribution and elimination. It is divided into two primary components: excretion and biotransformation.
Excretion refers to removing a drug from the body, either in its unchanged form or as its metabolites. Nonvolatile and polar drugs are primarily excreted through the kidneys, with other pathways including bile, sweat, saliva, and milk. Volatile drugs such as anesthetic gases are excreted via the...
2.4K
COPD: Pathogenesis and Clinical Features01:20

COPD: Pathogenesis and Clinical Features

1.7K
Chronic obstructive pulmonary disease (COPD) is a group of lung conditions that progressively worsen over time, including chronic bronchitis and emphysema. This cluster of diseases collectively leads to a gradual and irreversible decline in lung function over time.
The primary cause for the onset of COPD is cigarette smoking and exposure to air pollution. These hazardous factors initiate a chain reaction within the lungs, resulting in chronic inflammation, damage to the airways, and a...
1.7K
Loss of Tumor Suppressor Gene Functions01:12

Loss of Tumor Suppressor Gene Functions

5.8K
Tumor suppressor genes are normal genes that can slow down cell division, repair DNA mistakes, or program the cells for apoptosis in case of irreparable damage. Hence, they play an essential role in preventing the proliferation of damaged cells.
When the tumor suppressor genes develop mutations or are lost, cells start growing out of control, leading to cancer. However, a single functional copy of the tumor suppressor gene is enough for the cells to maintain their normal functions and cell...
5.8K

You might also read

Related Articles

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

Sort by
Same author

Large language models generate diagnostic likelihood ratios with low mean bias but wide dispersion.

Scientific reports·2026
Same author

Impedance reshaping control of LCL grid-connected inverters under weak grid conditions: digital delay compensation and robustness enhancement.

Scientific reports·2026
Same author

Safety of Cholecystectomy in Nonagenarians: A Systematic Review and Meta-Analysis.

Geriatrics (Basel, Switzerland)·2026
Same author

Green minds, sharp thoughts: How grass contact enhances cognitive performance and well-being in young adults.

Journal of behavior therapy and experimental psychiatry·2026
Same author

Cardiac Arrest During Interfacility Transport with Emergency Medical Services: A Preliminary Nationwide Cross-Sectional Study.

Prehospital emergency care·2026
Same author

Functional, molecular, and digital measurements of biological age.

The Journal of clinical investigation·2026

Related Experiment Video

Updated: Jan 10, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

16.4K

Entropy removal of clinical features.

Kian D Samadian1, Emma Chua2, Boyu Peng3

  • 1Department of Emergency Medicine, Massachusetts General Hospital, 55 Fruit St, Boston, MA, 02114, USA. ksamadian@mgb.org.

Scientific Reports
|November 23, 2025
PubMed
Summary

Quantifying diagnostic information using Shannon entropy reveals that most clinical features offer minor uncertainty reduction. However, a select group of high-impact findings significantly narrows diagnostic possibilities, correlating with established accuracy measures.

Keywords:
Clinical decision-makingDiagnostic performanceDiagnostic uncertaintyInformation theoryShannon entropyYouden’s index

More Related Videos

Enhancing Tumor Content through Tumor Macrodissection
10:04

Enhancing Tumor Content through Tumor Macrodissection

Published on: February 12, 2022

12.0K
Amplification of Near Full-length HIV-1 Proviruses for Next-Generation Sequencing
10:18

Amplification of Near Full-length HIV-1 Proviruses for Next-Generation Sequencing

Published on: October 16, 2018

12.6K

Related Experiment Videos

Last Updated: Jan 10, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

16.4K
Enhancing Tumor Content through Tumor Macrodissection
10:04

Enhancing Tumor Content through Tumor Macrodissection

Published on: February 12, 2022

12.0K
Amplification of Near Full-length HIV-1 Proviruses for Next-Generation Sequencing
10:18

Amplification of Near Full-length HIV-1 Proviruses for Next-Generation Sequencing

Published on: October 16, 2018

12.6K

Area of Science:

  • Medical Informatics
  • Information Theory
  • Diagnostic Decision Making

Background:

  • Clinical diagnosis relies on interpreting patient findings.
  • The diagnostic value of individual clinical features is often unclear.
  • Quantifying the information gained from each feature is crucial for improving diagnostic accuracy.

Purpose of the Study:

  • To quantify the diagnostic uncertainty reduction provided by individual clinical features using Shannon entropy.
  • To compare entropy reduction with traditional accuracy metrics like Youden's index and predictive values.
  • To identify high-performance features that offer substantial informational benefit in diagnosis.

Main Methods:

  • Analyzed 405 diverse clinical features (symptoms, signs, demographics, tests) from 23 systematic reviews.
  • Calculated Shannon entropy reduction from diagnostic tables for each feature.
  • Correlated entropy reduction with Youden's index and predictive values.

Main Results:

  • Most features provided modest uncertainty reduction; nearly half reduced uncertainty by less than 20%.
  • A subset of features achieved significant uncertainty reduction (>40%).
  • Entropy reduction showed strong positive correlations with Youden's index and positive predictive value.

Conclusions:

  • Shannon entropy offers a robust method to quantify the informational value of clinical findings.
  • Entropy analysis can highlight features with the greatest impact on reducing diagnostic uncertainty.
  • This approach can enhance clinical evaluation and diagnostic strategies by identifying key discriminative features.