scholarly journals Early Diagnosis of Pancreatic Ductal Adenocarcinoma by Combining Relative Expression Orderings With Machine-Learning Method

2020 ◽  
Vol 8 ◽  
Author(s):  
Zi-Mei Zhang ◽  
Jia-Shu Wang ◽  
Hasan Zulfiqar ◽  
Hao Lv ◽  
Fu-Ying Dao ◽  
...  
Keyword(s):  
Machine Learning ◽  
Early Diagnosis ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Ductal Adenocarcinoma ◽  
Machine Learning Method ◽  
Learning Method ◽  
Relative Expression ◽  
Relative Expression Orderings

802 PREDICTION OF EARLY RECURRENCE OF RESECTED PANCREATIC DUCTAL ADENOCARCINOMA: A MACHINE LEARNING METHOD

2020 ◽  
Vol 158 (6) ◽  
pp. S-1530
Author(s):  
Toshitaka Sugawara ◽  
Daisuke Ban ◽  
Jo Nishino ◽  
Tomotaka Kato ◽  
Atsushi Kudo ◽  
...  
Keyword(s):  
Machine Learning ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Early Recurrence ◽  
Ductal Adenocarcinoma ◽  
Machine Learning Method ◽  
Learning Method

scholarly journals Early Diagnosis of Hepatocellular Carcinoma Using Machine Learning Method

2020 ◽  
Vol 8 ◽  
Author(s):  
Zi-Mei Zhang ◽  
Jiu-Xin Tan ◽  
Fang Wang ◽  
Fu-Ying Dao ◽  
Zhao-Yue Zhang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Hepatocellular Carcinoma ◽  
Early Diagnosis ◽  
Machine Learning Method ◽  
Learning Method

Speech Organ Contour Extraction Using Real-Time MRI and Machine Learning Method

2019 ◽  
Author(s):  
Hironori Takemoto ◽  
Tsubasa Goto ◽  
Yuya Hagihara ◽  
Sayaka Hamanaka ◽  
Tatsuya Kitamura ◽  
...  
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Machine Learning Method ◽  
Learning Method ◽  
Contour Extraction

scholarly journals A Proteomic Study on the Personalized Protein Corona of Liposomes. Relevance for Early Diagnosis of Pancreatic DUCTAL Adenocarcinoma and Biomarker Detection

2021 ◽  
Vol 2 (2) ◽  
pp. 82-93
Author(s):  
Luca Digiacomo ◽  
Francesca Giulimondi ◽  
Daniela Pozzi ◽  
Alessandro Coppola ◽  
Vincenzo La Vaccara ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Early Diagnosis ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Protein Corona ◽  
Detection Sensitivity ◽  
Ductal Adenocarcinoma ◽  
Protein Biomarkers ◽  
Ca 19.9 ◽  
Proteomic Study

Due to late diagnosis, high incidence of metastasis, and poor survival rate, pancreatic cancer is one of the most leading cause of cancer-related death. Although manifold recent efforts have been done to achieve an early diagnosis of pancreatic cancer, CA-19.9 is currently the unique biomarker that is adopted for the detection, despite its limits in terms of sensitivity and specificity. To identify potential protein biomarkers for pancreatic ductal adenocarcinoma (PDAC), we used three model liposomes as nanoplatforms that accumulate proteins from human plasma and studied the composition of this biomolecular layer, which is known as protein corona. Indeed, plasma proteins adsorb on nanoparticle surface according to their abundance and affinity to the employed nanomaterial, thus even small differences between healthy and PDAC protein expression levels can be, in principle, detected. By mass spectrometry experiments, we quantified such differences and identified possible biomarkers for PDAC. Some of them are already known to exhibit different expressions in PDAC proteomes, whereas the role of other relevant proteins is still not clear. Therefore, we predict that the employment of nanomaterials and their protein corona may represent a useful tool to amplify the detection sensitivity of cancer biomarkers, which may be used for the early diagnosis of PDAC, with clinical implication for the subsequent therapy in the context of personalized medicine.

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