Efficient cancer classification by coupling semi supervised and multiple instance learning

HIGHLIGHTS

• who: ARNE SCHMIDT and colleagues from the of Computer Science Artificial Intelligence, University of Granada, Granada, Spain have published the research: Efficient Cancer Classification by Coupling Semi Supervised and Multiple Instance Learning, in the Journal: (JOURNAL)
• what: The authors propose evaluate an efficient labeling paradigm that guarantees a strong classification performance when combined with the learning framework. The authors compare the method to SSL MIL baselines the state-of-the-art completely supervised training. The authors propose a new machine_learning method based on MIL and SSL and an efficient labeling strategy to perform cancer classification . . .
  

   

  

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