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Related Concept Videos

Mouse Models of Cancer Study02:43

Mouse Models of Cancer Study

Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
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Mouse Models of Cancer Study02:43

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Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
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Enhanced Communication of Tumor Margins Using 3D Scanning and Mapping
07:47

Enhanced Communication of Tumor Margins Using 3D Scanning and Mapping

Published on: December 15, 2023

Mapping cancer for community engagement.

Kirsten M M Beyer1, Gerard Rushton

  • 1Dept of Geography, University of Iowa, Iowa City, IA 52242, USA. kirsten-beyer@uiowa.edu

Preventing Chronic Disease
|December 17, 2008
PubMed
Summary
This summary is machine-generated.

New disease mapping methods using geographic information systems (GIS) and community participation can help address health disparities. These tools provide localized cancer data, enabling communities to engage in reducing health inequities.

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Area of Science:

  • Public Health
  • Geographic Information Systems
  • Cancer Research

Background:

  • Health disparities can be reduced through community participation and geographic information systems (GIS).
  • Combining GIS with community participation, like disease mapping, can drive action against health disparities.
  • Current disease mapping often uses administrative units, limiting local cancer rate insights needed for community engagement.

Purpose of the Study:

  • To develop advanced disease mapping techniques for cancer research.
  • To create localized cancer incidence and late-stage diagnosis maps for community engagement.

Main Methods:

  • Utilized adaptive spatial filtering to generate continuous surface maps of late-stage colorectal cancer diagnoses.
  • Developed maps illustrating colorectal cancer incidence.
  • Collaborated with cancer researchers and practitioners.

Main Results:

  • Generated maps revealing distinct cancer patterns and their links to community contexts.
  • Maps are publicly accessible online and through partner organizations.
  • The developed maps offer localized insights into cancer distribution.

Conclusions:

  • Community-participatory research and GIS are increasingly utilized for disease mapping.
  • Effective engagement requires maps that accurately represent and contextualize local cancer data.
  • Accessible, context-rich disease maps are crucial for empowering communities to address cancer disparities.