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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
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Planning for learning involves the development of a teaching plan. Teaching plans are similar to nursing care plans—both follow the steps of the nursing process. Planning in the teaching process involves setting goals and outcomes. Here, goals identify what a patient needs to achieve to understand a healthcare topic better, whereas the outcomes are the action to be performed by the patient to achieve the goal within a timeframe. For example, if the goal is to educate the patient about...
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Traverse angle computations are a critical component of surveying, used to compute the internal angles within a closed traverse. A traverse consists of a series of connected lines forming a closed loop, often used for land boundary delineation or mapping. Calculating the internal angles ensures accuracy in the traverse geometry and is essential for checking survey data integrity.The process begins with known azimuths and bearings of the traverse sides. Internal angles at each vertex are...
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Nursing Process for Patient and Caregiver Teaching I: Assessment and Diagnosis01:24

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The nursing process provides a clinical decision-making framework for patients and families to establish and implement a personalized care plan. Since part of the nurse's duties is to teach patients, the steps of the nursing process are the most effective way to approach instruction. The nursing process and the teaching-learning process are inextricably linked.
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Area Computation by the Alternative Coordinate Method01:24

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The alternative coordinate method, also known as the Shoelace Formula, is a technique for determining the area of a traverse using Cartesian coordinates. This method relies on the sequential arrangement of x and y coordinates for each point of the shape, ensuring accuracy and ease of application.In this approach, each corner's x and y coordinates are listed as fractions, with the x-coordinate as the numerator and the y-coordinate as the denominator. These coordinates are arranged sequentially...
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Imaging Studies III: Computed Tomography01:27

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DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
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Basics of Multivariate Analysis in Neuroimaging Data
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Teaching Computational Reproducibility for Neuroimaging.

K Jarrod Millman1,2, Matthew Brett3, Ross Barnowski4

  • 1Division of Biostatistics, University of California, Berkeley, Berkeley, CA, United States.

Frontiers in Neuroscience
|November 9, 2018
PubMed
Summary
This summary is machine-generated.

This project-based course teaches reproducible neuroimaging analysis using computational tools like version control and code review. It fosters accuracy, efficiency, and collaboration, improving understanding of magnetic resonance imaging (MRI) techniques.

Keywords:
FMRIPython languagecomputational reproducibilitydata scienceeducationneuroimagingscientific computingstatistics

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Area of Science:

  • Neuroimaging
  • Computational Science
  • Scientific Education

Background:

  • Traditional neuroimaging education relies on lectures and software-based workshops.
  • This approach often results in superficial understanding and inefficient analysis methods.
  • There is a need for improved pedagogical methods in neuroimaging research.

Purpose of the Study:

  • To introduce a project-based learning model for reproducible and collaborative neuroimaging analysis.
  • To enhance students' understanding of foundational neuroimaging techniques and computational tools.
  • To promote efficient, accurate, and collaborative research practices.

Main Methods:

  • Developed and implemented a course centered around a substantial, open-ended group project.
  • Taught computational tools including Unix command line, structured code, version control, automated testing, and code review.
  • Focused on statistical techniques for basic magnetic resonance imaging (MRI) analysis.

Main Results:

  • The project-based approach successfully engaged students in reproducible research.
  • Students demonstrated improved understanding of computational tools and their importance for accuracy and efficiency.
  • The course effectively highlighted the value of collaboration in scientific analysis.

Conclusions:

  • A project-based model is effective for teaching reproducible and collaborative neuroimaging analysis.
  • This educational approach should form the basis for future neuroimaging programs.
  • The model serves as a template for teaching reproducible research in other computational science fields.