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

pV-Diagrams01:18

pV-Diagrams

4.3K
The pV diagram, which is a graph of pressure versus volume of the gas under study, is helpful in describing certain aspects of the substance. When the substance behaves like an ideal gas, the ideal gas equation describes the relationship between its pressure and volume. On a pV diagram, it is common to plot an isotherm, which is a curve showing p as a function of V with the number of molecules and the temperature fixed. Then, for an ideal gas, the product of the pressure of the gas and its...
4.3K
Interpreting X̄ Charts01:13

Interpreting X̄ Charts

104
Interpreting x̄ charts, a type of control chart used in statistical process control helps monitor the variation in processes over time. The x̄ chart is based on the sample mean and allows for monitoring variations in the process mean over time. These charts are pivotal for quality assurance in manufacturing and other sectors.
An x̄ chart plots the values of individual measurements over time against control limits calculated from historical data. The central line...
104
¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

1.1K
When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
1.1K
Super-resolution Fluorescence Microscopy01:37

Super-resolution Fluorescence Microscopy

7.1K
Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been...
7.1K

You might also read

Related Articles

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

Sort by
Same author

From the Page to the Plate: Designing an Accessible Nutrition Resource Through Community-Engaged Research.

Global advances in integrative medicine and health·2026
Same author

Response to Letter to the Editor: "Recurrence and mortality after Pseudomonas aeruginosa bloodstream infection".

European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology·2026
Same author

Conceptualisation of survival after critical illness using Institution-free days as a composite primary outcome by intensive care unit survivors and clinicians: A qualitative study using framework analysis.

Australian critical care : official journal of the Confederation of Australian Critical Care Nurses·2026
Same author

The impact of sex on therapy, epidemiology, and outcome in bloodstream infections.

Expert review of anti-infective therapy·2026
Same author

The Queensland Bloodstream Infections (QBSI) study: rationale, protocol development and future directions.

Infectious diseases (London, England)·2026
Same author

A mixed-methods longitudinal observational study exploring physical activity during pregnancy in women with pre-existing diabetes, support needs and associations with diabetes management: a study protocol.

BMJ open·2026
Same journal

Real-time EEG-based epileptic seizure prediction using artificial intelligence: A systematic review.

Artificial intelligence in medicine·2026
Same journal

R-peak detection and ECG data compression scheme based on empirical mode decomposition and wavelet transform.

Artificial intelligence in medicine·2026
Same journal

CastNet: A three-channel EEG-based deep learning model for cross-subject depression detection.

Artificial intelligence in medicine·2026
Same journal

State-of-the-art TinyML approaches for colorectal cancer detection: Current advances, challenges, and future directions.

Artificial intelligence in medicine·2026
Same journal

JRadiEvo: A Japanese radiology report generation model enhanced by evolutionary optimization of model merging.

Artificial intelligence in medicine·2026
Same journal

Causally-informed deep learning towards explainable and generalizable outcome prediction in critical care.

Artificial intelligence in medicine·2026
See all related articles

Related Experiment Video

Updated: Aug 23, 2025

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
10:58

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

Published on: January 2, 2011

10.2K

xPM: Enhancing exogenous data visibility.

Adam Banham1, Sander J J Leemans2, Moe T Wynn1

  • 1Queensland University of Technology, Brisbane, Queensland, Australia.

Artificial Intelligence in Medicine
|November 3, 2022
PubMed
Summary
This summary is machine-generated.

Integrating contextual (exogenous) data with process mining enhances healthcare insights. This approach links patient data and behaviors to outcomes, revealing trends not visible with standard methods.

Keywords:
Exogenous dataMIMIC-IIIMulti-perspectiveProcess mining

More Related Videos

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma
09:17

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma

Published on: September 13, 2022

2.4K
Visualizing Intracellular Sialylation with Click Chemistry and Expansion Microscopy
08:16

Visualizing Intracellular Sialylation with Click Chemistry and Expansion Microscopy

Published on: February 7, 2025

548

Related Experiment Videos

Last Updated: Aug 23, 2025

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
10:58

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

Published on: January 2, 2011

10.2K
Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma
09:17

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma

Published on: September 13, 2022

2.4K
Visualizing Intracellular Sialylation with Click Chemistry and Expansion Microscopy
08:16

Visualizing Intracellular Sialylation with Click Chemistry and Expansion Microscopy

Published on: February 7, 2025

548

Area of Science:

  • Health Informatics
  • Data Science
  • Process Science

Background:

  • Process mining typically uses only internal process data (endogenous).
  • Limited research explores integrating external contextual data (exogenous) into process mining.
  • Existing methods often overlook the impact of exogenous factors on process outcomes.

Purpose of the Study:

  • To develop a framework for process mining incorporating exogenous data.
  • To introduce novel analyses linking exogenous data, process behavior, and outcomes.
  • To demonstrate the practical application and benefits of this integrated approach in healthcare.

Main Methods:

  • Developed a framework for integrating exogenous data into process mining.
  • Created new analytical methods to visualize and link exogenous data with process behavior and outcomes.
  • Applied the framework and analyses to the MIMIC-III healthcare dataset.

Main Results:

  • The combination of endogenous and exogenous data yields deeper insights than standard process mining.
  • New analyses effectively visualize exogenous data trends and variations related to outcomes.
  • Clinicians can extract meaningful insights from patient vital signs (exogenous data) linked to clinical outcomes.

Conclusions:

  • Process mining can successfully integrate large volumes of physiological data and interventions.
  • The developed methods enable the conversion of complex data into clinically interpretable information.
  • Integrating exogenous data significantly enhances the value and applicability of process mining in healthcare.