2023 Fiscal Year Research-status Report
Multivariate machine learning analysis for identyfing neuro-anatomical biomarkers of anorexia and classifying anorexia subtypes using MR datasets.
Project/Area Number |
23K14813
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Research Institution | Chiba University |
Principal Investigator |
BhusalChhatkuli Ritu 千葉大学, 子どものこころの発達教育研究センター, 特任助教 (50836591)
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Project Period (FY) |
2023-04-01 – 2026-03-31
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Keywords | Anorexia / Classification / MRI / Biomarkers / Machine Learning |
Outline of Annual Research Achievements |
The purpose of this research is to classify anorexia nervosa (AN) from healthy controls using structural MR images and to identify the neuro anatomical biomarkers of anorexia. The first step of research is completed with successful classification using machine learning algorithms such as gradient boosting and Boruta with random forest. Results have been presented in the cognitive behavioral therapy conference (EABCT 2023, Antalya ,Turkey).A research paper has been submitted and is under review.
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Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
Initial stage of the research went smoothly with significant results already submitted to the scientific journal.
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Strategy for Future Research Activity |
In future, once the paper is accepted, second phase of the research will start with more number of patient data set, and pre and post MR images for the prediction of treatment response. Also, classification of other eating and psychological disorders such as Bulimia Nervosa, Obsessive compulsive disorders will be analyzed.
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Causes of Carryover |
This year the volunteers study used were already recruited for some other projects and since it was initial study the calculations were performed in existing machines. However, for next Fiscal year, the amount will be used for recruiting volunteers, buying advanced calculating server, attending conferences and Journal publishing fees etc.
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Research Products
(1 results)