Data Analysis! I’m interested in data analysis that help everyone.
https://indify.co/widgets/live/button/Xet1KlxMvqOrD3BNTWpI
Hi, there! I’m a senior at Kyung Hee University, Department of Software Convergence and researcher at Medical IP, Department of Research & Science. My major study is concentrated in Medical Data Science.
My focus area is on the convergence of medical data analysis, human-centered AI interaction, qualitative, quantitative project experiments. Recently, I am building up experience through processing data and implementing AI model by executing projects.
**** My final goal is to find the best solution based on my experience and research and become a data analyst who positively affects everyone involved in the field through it. In order to achieve my goal, I am trying to make up for deficiencies, build up more experience today!
| May 2023 | [NEW] Join Medical IP - Medical Imaging AI Solutions and Product Development Company, leveraging patients' medical big data including CT, MRI, X-ray, Medical IP |
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| Dec 2022 | Grand Prize - Medical Information Data Analysis Expert Intensive Course II Team Project Contest, Seoul Asan Medical Center |
| Oct 2022 | Follow the Curriculum - Medical Information Data Analysis Expert Intensive Course II, Seoul Asan Medical Center |
| Sep 2022 | Advanced to the Finals - Software-Centered University joint AI Competition, Ministry of Science and ICT |
| Jan 2022 | Participation Prize - Korea Software Congress (KSC2021), Korean Institute of Information Scientists and Engineers |
| Dec 2021 | Paper Presentation - Korea Software Congress (KSC2021), Korean Institute of Information Scientists and Engineers |
Data Science track, Department of Software Convergence.
12th Graduates. (Science Core High School)
Degree Research & Dissertation (September 2021 ~ January 2022)
In this study, the performance of various convolutional neural network (CNN) based brain age prediction models was compared and evaluated using structural T1 weighted MRI data. We used Mean Absolute Error (MAE) and correlation (R) of actual age and predicted brain age as evaluation metrics. [Readme]
Awarded at Korea Software Congress 2021 (KSC2021).
Python, Google Colab
https://github.com/HJK02130/A-Performance-Evaluation-of-CNN-for-Brain-Age-Prediction-Using-Structural-MRI-Data