A comparison of computer-aided diagnosis schemes optimized using radiomics and deep transfer learning methods

HIGHLIGHTS

• who: Gopichandh Danala and colleagues from the School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, USA have published the paper: A Comparison of Computer-Aided Diagnosis Schemes Optimized Using Radiomics and Deep Transfer Learning Methods, in the Journal: Bioengineering 2022, 9, 256. of 13/06/2022
• what: This study shows that using deep transfer learning is more efficient to develop CAD schemes and it enables a higher lesion classification performance than CAD schemes developed using radiomicsbased technology. The authors focus on developing computer-aided diagnosis schemes of mammograms to help improve accuracy . . .
  

   

  

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