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

Critical Thinking II01:25

Critical Thinking II

Critical thinking is a cognitive process with several attributes. The attributes of critical thinking include the following:
Reasoning01:30

Reasoning

Reasoning is the action of thinking about something in a logical, sensible way. It is integral to problem-solving, decision-making, and critical thinking. Reasoning can be inductive or deductive. Reasoning involves transforming information into conclusions, which is essential for problem-solving, decision-making, and critical thinking.
Inductive reasoning involves deriving generalizations from specific observations. This type of reasoning helps form beliefs about the world. For example,...
Mason's Rule01:20

Mason's Rule

Mason's rule is a powerful tool in control systems and signal processing. It simplifies the calculation of transfer functions from signal-flow graphs. This method leverages various elements, including loop gains, forward-path gains, and non-touching loops, to determine the transfer function efficiently.
Loop gain is determined by identifying and tracing a path from a node back to itself. This involves computing the product of branch gains along the loop. Each loop's gain is crucial for further...
Deductive Reasoning01:16

Deductive Reasoning

Deductive reasoning, or deduction, is the type of logic used in hypothesis-based science. In deductive reasoning, the pattern of thinking moves in the opposite direction from inductive reasoning. It uses a general principle or law to predict specific results. From these general principles, a scientist can predict specific results that remain valid as long as the general principles are correct.For example, a researcher can make specific predictions from the hypothesis "butterflies are attracted...
Rules for Defining Functions01:29

Rules for Defining Functions

A relation is a function if each input x is associated with exactly one output y. For example, the equation      y = 2x + 5 defines a function because every value of x yields a unique y. However, x = y² + 1 is not a function of x, since a single x-value, such as x = 2, corresponds to two possible y-values: y = 1 and y = -1.The vertical line test helps determine whether a graph represents a function. If a vertical line intersects a curve more than once, the curve fails the test and does not...
Decision Making: Traditional Method01:14

Decision Making: Traditional Method

The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...

You might also read

Related Articles

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

Sort by
Same author

The association between hypoxic burden and bronchopulmonary dysplasia in preterm infants: a retrospective cohort study.

Pediatric research·2026
Same author

Prediction of Obstetric Anal Sphincter Injury in Nulliparous Women: Model Development and Temporal Validation.

BJOG : an international journal of obstetrics and gynaecology·2026
Same author

Socioeconomic differences in older adults' intention to use mhealth applications.

BMC geriatrics·2026
Same author

The Evaluation of Transformer Models for the Detection of Adverse Drug Events: A Benchmark Study Using Dutch Free-Text Documents of Hospitalized Patients.

Drug safety·2026
Same author

Education attainment at age 25 after induction of labor versus non-intervention at term: a population-based linked cohort study.

European journal of obstetrics, gynecology, and reproductive biology·2026
Same author

The association of environmental exposure with multiple sclerosis severity score: A study based on sequential data modeling.

International journal of medical informatics·2026

Related Experiment Video

Updated: Jun 4, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

LERM (Logical Elements Rule Method): a method for assessing and formalizing clinical rules for decision support.

Stephanie Medlock1, Dedan Opondo, Saeid Eslami

  • 1Department of Medical Informatics, Academic Medical Center, Meibergdreef 15, 1105 AZ Amsterdam, The Netherlands. s.k.medlock@amc.uva.nl

International Journal of Medical Informatics
|February 22, 2011
PubMed
Summary

A new 7-step method, the Logical Elements Rule Method, was developed and validated for transforming clinical rules into decision support systems. It proved usable and reliable for formalizing rules for implementation.

Related Experiment Videos

Last Updated: Jun 4, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Area of Science:

  • Clinical Informatics
  • Health Services Research

Background:

  • Clinical decision support systems (CDSS) require formalized clinical rules for effective implementation.
  • Existing methods for rule transformation may lack systematic approaches for usability and reliability.

Purpose of the Study:

  • To develop a step-by-step method for transforming clinical rules for CDSS.
  • To validate the usability and reliability of the developed method.

Main Methods:

  • A literature review identified clinical rules.
  • An iterative approach with a mixed-expert focus group developed the rule transformation method.
  • Two independent assessors applied the method to a validation set of rules.
  • Usability assessed via time and error rates; reliability assessed via inter-assessor agreement.

Main Results:

  • The Logical Elements Rule Method (LERM) comprises 7 steps for rule assessment and formalization.
  • LERM is usable across diverse clinical rules and conditions.
  • Reliability is achieved when users agree on terminology and evaluation timing.

Conclusions:

  • A validated, usable, and reliable method (LERM) facilitates the transformation of clinical rules for CDSS.
  • LERM aids developers in creating effective rule-based decision support.
  • Standardized terminology enhances reliability but may increase error rates.