📌 Note: This study is currently ongoing, and I am participating as a researcher at the Artificial Intelligence Convergence Institute at Sungkyunkwan University.
- Platform Development and Proof of High Trust & Optimal Response Time Processing for Heterogeneous, Atypical Data and Large Scaled Data in 5G-IoT Environment
- Early detection of benign/malignant tumors is crucial, and conventional diagnostic methods may not be sufficient. As a result, recent technological advancements have led to active research on using wireless signals to differentiate objects, and this technology can be leveraged to detect benign/malignant tumors, as early detection of these tumors is crucial and conventional diagnostic methods may not be sufficient.
- The objective of this study is to develop a model for detecting benign/malignant tumors using wireless signals. I will perform analysis on wireless signal data and utilize various machine learning algorithms and deep learning techniques, with a focus on analyzing RF signals, to develop a model that can differentiate between benign and malignant tumors in tissues.
- Currently, our research team is collecting data using models that simulate human skin tissue and tumor tissue, and I am performing tasks to train and evaluate simple classification models such as SVM, KNN, C5.0, MLP, and MiniRocket to analyze the correlations between the data and obtain reliability. Based on this, I aim to develop a machine learning model that can contribute to early detection and treatment of benign/malignant tumors by obtaining permission to collect real patient data from Bundang Seoul National University Hospital.
