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Related Concept Videos

Radiological Investigation I: X-ray and CT01:30

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Radiological investigations, including X-rays and computed tomography (CT) scans, are critical for diagnosing and evaluating various medical conditions. These imaging techniques provide valuable insights into the body's internal structures, aiding in the detection of abnormalities, assessment of disease progression, and development of treatment strategies. This article delves into two primary radiological investigations, chest X-rays and CT scans, outlining their purpose, procedures, and...
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The function of adult-born mammalian neurons remains an active area of investigation. Ionizing radiation inhibits the birth of new neurons. Using computer tomography-guided focal irradiation (CFIR), three-dimensional anatomical targeting of specific neural progenitor populations can now be used to assess the functional role of adult...
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Radiological Investigation II: MRI and Ventilation Perfusion Scan01:30

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Description
Magnetic Resonance Imaging (MRI) and Ventilation Perfusion Scans are two radiological investigations that offer detailed diagnostic images of the body, particularly lung structures.
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MRI uses magnetic fields and radiofrequency signals to distinguish between normal and abnormal tissues. This technology provides a more detailed diagnostic image than CT scans, enabling it to characterize pulmonary nodules, stage bronchogenic carcinoma, and evaluate inflammatory activity in...
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Radiological Investigation III: Pulmonary Angiogram and PET Scan01:13

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Radiological investigations are paramount in the diagnosis and management of various pulmonary diseases. Two essential investigations are the Pulmonary Angiogram and the Positron Emission Tomography (PET) Scan.
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Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
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A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
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Updated: Jan 19, 2026

Functional Interrogation of Adult Hypothalamic Neurogenesis with Focal Radiological Inhibition
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Big Data and Radiology Research.

Etta D Pisano1, Leah R Garnett2

  • 1American College of Radiology, Reston, Virginia; Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts.

Journal of the American College of Radiology : JACR
|September 8, 2019
PubMed
Summary
This summary is machine-generated.

Digitized health data and artificial intelligence (AI) offer new ways to generate research hypotheses and improve patient care. Professionals must develop new skills in data science for future healthcare advancements.

Keywords:
Artificial intelligencebig dataradiology research

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Area of Science:

  • Health Informatics
  • Artificial Intelligence in Medicine
  • Data Science

Background:

  • The increasing volume of digitized health data presents opportunities for advancing medical research and patient care.
  • Traditional research methods like observational studies and randomized trials are complemented by big data analytics.
  • The National Institutes of Health's 2018 Strategic Plan for Data Science emphasizes leveraging big data for research discoveries.

Purpose of the Study:

  • To highlight the potential of big data and artificial intelligence (AI) in enhancing human health understanding.
  • To underscore the shift towards data-driven hypothesis generation in medical research.
  • To emphasize the need for new skills among researchers and physicians in data science and AI.

Main Methods:

  • Utilizing the unprecedented volume of digitized healthcare data.
  • Applying artificial intelligence (AI) to mine data for correlations and patterns.
  • Analyzing big data to reveal associations for further research.

Main Results:

  • Identification of new research hypotheses through data mining.
  • Potential for improved patient care strategies based on data-driven insights.
  • Demonstration of big data's role in stimulating novel research discoveries.

Conclusions:

  • Digitized health data and AI are poised to significantly advance our understanding of human health.
  • A paradigm shift in medical research is occurring, integrating data science and AI.
  • Continuous learning and skill development in data collection, mining, and AI application are crucial for healthcare professionals.