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Related Concept Videos

Types of Reports II: Incident or Occurrence Report01:21

Types of Reports II: Incident or Occurrence Report

An Incident or Occurrence Report in a healthcare setting is a crucial document used to record any unexpected occurrence that may or may not have affected a patient, employee, or visitor. Such reports are critical to improving patient safety and include all details leading up to and including the event.
Purposes:
In the healthcare industry, reports play a crucial role in documenting incidents within an agency. The primary objective of these reports is to ensure patient safety, uphold the...
Data Reporting and Recording01:24

Data Reporting and Recording

Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
X-ray Imaging01:24

X-ray Imaging

German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with X-rays, and by 1900, X-ray was widely...
Positron Emission Tomography01:29

Positron Emission Tomography

Positron emission tomography (PET) is a medical imaging technique involving radiopharmaceuticals — substances that emit short-lived radiation. Although the first PET scanner was introduced in 1961, it took 15 more years before radiopharmaceuticals were combined with the technique and revolutionized its potential.
One of the main requirements of a PET scan is a positron-emitting radioisotope, which is produced in a cyclotron and then attached to a substance used by the part of the body being...

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Related Experiment Video

Updated: Jun 1, 2026

Clinical Imaging of Microwave Mammography
05:28

Clinical Imaging of Microwave Mammography

Published on: November 14, 2025

Characterizing mammography reports for health analytics.

Carlos C Rojas1, Robert M Patton, Barbara G Beckerman

  • 1Oak Ridge National Lab, Oak Ridge, TN 37831-6085, USA. rojascc@ornl.gov

Journal of Medical Systems
|June 15, 2011
PubMed
Summary

Large-scale analysis of digital health data, particularly free-text mammography reports, enables evidence-based public health and patient-centric care. This study details transforming raw data into an analytics-ready collection and presents a generic system architecture for clinical note analysis.

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Related Experiment Videos

Last Updated: Jun 1, 2026

Clinical Imaging of Microwave Mammography
05:28

Clinical Imaging of Microwave Mammography

Published on: November 14, 2025

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

Area of Science:

  • Medical Informatics
  • Data Science
  • Public Health

Background:

  • Increasing availability of massive digital health datasets.
  • Potential for automated analysis to advance public health and patient care.
  • Need for structured, accessible data for large-scale health analytics.

Purpose of the Study:

  • To transform unstructured, free-text mammography data into a searchable collection for analytics.
  • To develop and apply methods for characterizing and analyzing this health data.
  • To present a generic system architecture for health analytics from clinical notes.

Main Methods:

  • Information retrieval techniques.
  • Supervised machine learning algorithms.
  • Classical statistical analysis.
  • Temporal data analysis.

Main Results:

  • Successful transformation of raw mammography data into an analytics-ready collection.
  • Demonstrated validity and utility of analytical methods through experimental results.
  • Generated insights consistent with known data features and revealed novel findings.

Conclusions:

  • The described approach effectively enables large-scale health analytics from clinical notes.
  • The developed system architecture provides a blueprint for generic health data analysis.
  • This work supports the vision of evidence-based public health and patient-centric healthcare.