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Related Concept Videos

Radiation: Applications01:17

Radiation: Applications

1.9K
The average temperature of Earth is the subject of much current discussion. Earth is in radiative contact with both the Sun and dark space; it receives almost all its energy from the radiation of the Sun and reflects some of it into outer space. Dark space is very cold, about 3 K, so Earth radiates energy into it. For instance, heat transfer occurs from soil and grasses, the rate of which can be so rapid that frost can occur on clear summer evenings, even in warm latitudes.
The average...
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Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant
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[Big data, generalities and integration in radiotherapy].

C Le Fèvre1, L Poty2, G Noël3

  • 1Département universitaire de radiothérapie, centre Paul-Strauss, unicancer, 3, rue de la Porte-de-l'Hôpital, 67065 Strasbourg cedex, France.

Cancer Radiotherapie : Journal De La Societe Francaise De Radiotherapie Oncologique
|November 19, 2017
PubMed
Summary
This summary is machine-generated.

Big data in health accelerates discoveries and optimizes patient management. In radiotherapy, this approach aims to predict treatment effectiveness and tolerance, paving the way for personalized medicine.

Keywords:
Big dataCancerGenomicsGénomiqueModèle prédictifPredictive modelRadiosensibilitéRadiosensitivityRadiotherapyRadiothérapie

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Area of Science:

  • Health Informatics
  • Medical Physics
  • Oncology

Background:

  • Advances in data collection and computing systems have led to a surge in health data volume and diversity.
  • Big data analytics offers potential for accelerating medical discoveries and improving patient management through advanced modeling.

Purpose of the Study:

  • To explore the application of big data in radiotherapy for predicting treatment outcomes.
  • To highlight the potential of big data in developing personalized medicine for radiation therapy.

Main Methods:

  • Leveraging large and heterogeneous datasets in radiotherapy, including demographics, radiomics, genomics, and radiogenomics.
  • Developing predictive therapeutic models using big data analytics.

Main Results:

  • Big data enables the integration of diverse health information for enhanced analysis.
  • Heterogeneous data in radiotherapy holds promise for predicting treatment effectiveness and tolerance.

Conclusions:

  • Big data presents a significant opportunity to advance radiotherapy research and clinical practice.
  • The integration of big data is crucial for the future of personalized, secure, and reliable radiation therapy.