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Outcome Prediction after Radiotherapy with Medical Big Data.
Magome, Taiki.
Affiliation
  • Magome T; Department of Radiological Sciences, Faculty of Health Sciences, Komazawa University.
Igaku Butsuri ; 36(1): 39-41, 2016.
Article in Ja | MEDLINE | ID: mdl-28428496
Data science is becoming more important in many fields. In medical physics field, we are facing huge data every day. Treatment outcomes after radiation therapy are determined by complex interactions between clinical, biological, and dosimetrical factors. A key concept of recent radiation oncology research is to predict the outcome based on medical big data for personalized medicine. Here, some reports, which are analyzing medical databases with machine learning techniques, were reviewed and feasibility of outcome prediction after radiation therapy was discussed. In addition, some strategies for saving manual labors to analyze huge data in medical physics were discussed.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Radiotherapy Type of study: Guideline / Prognostic_studies / Risk_factors_studies Limits: Humans Language: Ja Journal: Igaku Butsuri Journal subject: BIOFISICA Year: 2016 Type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Radiotherapy Type of study: Guideline / Prognostic_studies / Risk_factors_studies Limits: Humans Language: Ja Journal: Igaku Butsuri Journal subject: BIOFISICA Year: 2016 Type: Article