2017 Fiscal Year Final Research Report
Prediction of Recurrence of Liver Cancer by a Discrete Bayes Decision Rule for Personalized Medicine
| Project/Area Number |
15K00238
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Multi-year Fund |
|---|
| Section | 一般 |
|---|
| Research Field |
Perceptual information processing
|
|---|
| Research Institution | Yamaguchi University |
|---|
Principal Investigator |
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
飯塚 徳男 広島大学, 医歯薬保健学研究科(薬), 教授 (80332807)
藤田 悠介 山口大学, 大学院創成科学研究科, 准教授 (40509527)
|
|---|
| Project Period (FY) |
2015-04-01 – 2018-03-31
|
| Keywords | パターン認識 / 癌 / 診断 |
|---|
| Outline of Final Research Achievements |
The refractory problem lies in the high percentage of recurrence of liver cancer: about 30% of postoperative patients experience recurrence within one year. The purpose of this study is to distinguish between the presence and absence of recurrence with a high degree of accuracy by using our discrete Bayes decision rule that can handle discrete data. Discrimination performance of the discrete Bayes decision rule using the optimal combination of markers against test samples showed a sensitivity of 86% and specificity of 49%. Moreover, the discrete Bayes decision rule was applied to diagnose lymph node metastasis for early gastric cancer. The proposed method was able to differentiate lymph node metastasis with 100% sensitivity and 86% specificity. These results suggest that the proposed method might lead to clinical applications.
|
| Free Research Field |
情報工学
|
