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

Survival Tree01:19

Survival Tree

86
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
86
Phylogenetic Trees03:21

Phylogenetic Trees

45.3K
Phylogenetic trees come in many forms. It matters in which sequence the organisms are arranged from the bottom to the top of the tree, but the branches can rotate at their nodes without altering the information. The lines connecting individual nodes can be straight, angled, or even curved.
45.3K
Heuristics01:21

Heuristics

93
Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
93
Levels of Use of a GIS01:29

Levels of Use of a GIS

52
Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
52
Manipulation and Analysis01:21

Manipulation and Analysis

26
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
26

You might also read

Related Articles

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

Sort by
Same author

Electroacupuncture Protects Against Post-MI Heart Failure Through Autonomic Regulation and α7nAChR Activation.

Cardiology research and practice·2026
Same author

Inhalable extracellular vesicle delivered IL-10 mRNA attenuates pulmonary hypertension in rats.

Journal of nanobiotechnology·2026
Same author

Tracing the stemness and malignant transition in a heritable colorectal cancer Lynch Syndrome by single-cell RNA-seq analysis.

Frontiers in immunology·2026
Same author

Adipokine Nesfatin-1 Mediates Endothelial Dysfunction by Suppressing <i>MEF2B</i>/<i>BMPR1A</i> During Pulmonary Vascular Remodeling.

Journal of the American Heart Association·2026
Same author

Ovarian Mucinous Neoplasms Associated With Mesonephric-like Lesions: An Updated Study With Novel Pathologic Features.

The American journal of surgical pathology·2026
Same author

Guidelines and consensus for minimal residual disease-adapted therapy in multiple myeloma from the Pan-Pacific multiple myeloma working group.

Clinical hematology international·2026

Related Experiment Video

Updated: Jul 6, 2025

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

8.7K

Improved adaptive-phase fuzzy high utility pattern mining algorithm based on tree-list structure for intelligent

Jing Chen1,2, Aijun Liu2, Hongjun Zhang1

  • 1School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, 210023, China.

Scientific Reports
|January 10, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces an Improved fuzzy high-utility pattern mining (IF-HUPM) algorithm to enhance pattern interpretability in medical AI decision-making. The novel approach improves accuracy and efficiency for discovering meaningful diagnostic patterns.

More Related Videos

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.5K
Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.7K

Related Experiment Videos

Last Updated: Jul 6, 2025

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

8.7K
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.5K
Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.7K

Area of Science:

  • Artificial Intelligence
  • Data Mining
  • Medical Informatics

Background:

  • Computerized medical decision-making is advancing rapidly with AI and big data.
  • High-utility pattern mining (HUPM) aims to find diagnostic patterns in medical data.
  • Existing HUPM methods often lack interpretability and explainability for clinical use.

Purpose of the Study:

  • To propose a novel algorithm, Improved fuzzy high-utility pattern mining (IF-HUPM), to address the interpretability limitations of HUPM.
  • To enhance the meaningfulness and explainability of patterns discovered in medical databases for diagnosis.
  • To improve the accuracy and efficiency of pattern mining in medical decision-making.

Main Methods:

  • Applied a fuzzy preprocessing method to segment quantitative medical data into fuzzy intervals, improving data fuzziness and interpretability.
  • Utilized fuzzy tree and list structures within the IF-HUPM algorithm to compute fuzzy high-utility values.
  • Developed an adaptive-phase Fuzzy HUPM hybrid framework by integrating characteristics of one-stage and two-stage HUPM algorithms.

Main Results:

  • The IF-HUPM algorithm demonstrated enhanced accuracy and efficiency in discovering high-utility patterns.
  • The mining process using IF-HUPM required less computational time and memory on average.
  • Experimental results validated the effectiveness of the fuzzy preprocessing and hybrid framework.

Conclusions:

  • The proposed IF-HUPM algorithm effectively addresses the interpretability challenge in HUPM for medical decision-making.
  • IF-HUPM offers a more accurate, efficient, and interpretable approach to mining valuable diagnostic patterns from medical data.
  • This research contributes to advancing explainable AI in healthcare through improved pattern mining techniques.