###### Abstract  
An accuracy of \(\geq\)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, small-scale target domain data, which are collected to achieve our objective, are inputted directly into a model constructed with source domain data which are collected from a different domain from the target; target vectors are estimated with the outputted target domain data and applied to refine the model. Recognition performance of small-scale data is improved by reusing all layers, including the output layers of the neural network. Proteomics is generally considered the ultimate bio-diagnostic technique and provides extremely high information density in its two-dimensional electrophoresis images, but extracting the data has posed a basic problem. The present study is expected to solve that problem and will be an important breakthrough for practical utilization and future perspectives of proteomics in clinics after evaluation in clinical settings. protomics; artificial intelligence; sepsis classification; deep neural network; transfer learning +
Footnote †: journal: Medical Imaging  
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Footnote 1: School of Life Science and Technology, Tokyo Institute of Technology, 2-12-1, Ookayama, Meguro-ku, Tokyo 152-8550, Japan; [EMAIL_ADDRESS]  
[PERSON]  
1 School of Life Science and Technology, Tokyo Institute of Technology, 2-12-1, Ookayama, Meguro-ku, Tokyo 152-8550, Japan; yamsaguchi.60 [EMAIL_ADDRESS]  
[PERSON]  
3 School of Life Science and Technology, Tokyo Institute of Technology, 2-12-1, Ookayama, Meguro-ku, Tokyo 152-8550, Japan; [EMAIL_ADDRESS]  
[PERSON]  
4 Business Innovation Division, Panasonic Corporation, Tokyo Fashion Town West, 3-4-10 Ariake Koto-ku, Tokyo 135-8072, Japan; [EMAIL_ADDRESS] (Y.S. ); [EMAIL_ADDRESS] (T.N.) [PERSON]  
5 Nihon University Surugadai Hospital, 1-6 Kanda-Surugadai, Chiyoda-ku, Tokyo 101-8309, Japan; [EMAIL_ADDRESS]  
[PERSON]  
3 School of Life Science and Technology, Tokyo Institute of Technology, 2-12-1, Ookayama, Meguro-ku, Tokyo 152-8550, Japan; yamsaguchi.60 [EMAIL_ADDRESS]
[PERSON]  
3 School of Life Science and Technology, Tokyo Institute of Technology, 2-12-1, Ookayama, Meguro-ku, Tokyo 152-8550, Japan; [EMAIL_ADDRESS]  
[PERSON]  
4 Business Innovation Division, Panasonic Corporation, 1006 Kadoma, Kadoma City, Osaka 571-8501, Japan; [EMAIL_ADDRESS]  
[PERSON]  
6 Department of Emergency and Disaster Medicine, Juntendo University Graduate School of Medicine, 2-1-1, Hongo, Bunkyo-ku, Tokyo 113-8421, Japan; [EMAIL_ADDRESS]  
[PERSON]  
4 Business Innovation Division, Panasonic Corporation, 1006 Kadoma, Kadoma City, Osaka 571-8501, Japan; [EMAIL_ADDRESS]  
[PERSON]  
6 Department of Emergency and Disaster Medicine, Juntendo University Graduate School of Medicine, 2-1-1, Hongo, Bunkyo-ku, Tokyo 113-8421, Japan; toshiba@juntendo. procedures involved require skill and time, it can be difficult to obtain large amounts of high-quality data. This is a practical reason why 2D-GE has not been used for clinical diagnoses, even though proteomics is the most powerful method available for profiling of organisms [1]. Recently, we developed a high-performance two-dimensional polyacrylamide gel electrophoresis (HP-2D-PAGE) technique with high throughput, high sensitivity, and high reproducibility [2]. In this procedure, the first dimensional and second dimensional gel whose size is smaller than that for usual two-dimensional electrophoresis was used because the stabilities of electric field, voltage, and temperature should be maintained. If these stabilities are lost, the focuses of spots on the gel will be lost. Additionally, loose focus will result in deterioration for resolutions of the spots and sensitivities of the signals.