Diagnosis of Sepsis by AI-Aided Proteomics Using 2D Electrophoresis Images of Patient Serum Incorporating Transfer Learning for Deep Neural Networks

Diagnosis of Sepsis by AI-Aided Proteomics Using 2D Electrophoresis Images of Patient Serum Incorporating Transfer Learning for Deep Neural Networks

An accuracy of ≥98% was achieved in sepsis diagnosis using serum samples from 30 sepsis patients and 68 healthy individuals and a high-performance two-dimensional polyacrylamide gel electrophoresis (HP-2D-PAGE) method developed here with deep learning and transfer learning algorithms. In this method...

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Bibliographic Details
Main Authors: Nobuhiro Hayashi, Yoshihide Sawada, Kei Ujimoto, Syunta Yamaguchi, Yoshikuni Sato, Takahiro Miki, Toru Nakada, Toshiaki Iba
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Applied Sciences
Subjects:
proteomics
artificial intelligence
sepsis classification
deep neural network
transfer learning
Online Access:https://www.mdpi.com/2076-3417/11/4/1967

Internet

https://www.mdpi.com/2076-3417/11/4/1967

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