Publications by authors named "Yunxi Ge"
Article Synopsis
- Temperature prediction is important for liver cancer treatment as it helps determine the coagulation zone during microwave ablation.
- Experiments were conducted on porcine liver tissues using machine learning (random forests) to create accurate temperature prediction models, with results showing low average absolute errors for different power settings.
- The proposed model outperforms traditional imaging methods in measuring coagulation area and can interpret relevant texture features, making it valuable for clinical applications in microwave ablation.
Oxidative stress is crucial to the biology of tumors. Oxidative stress' potential predictive significance in colorectal cancer (CRC) has not been studied; nevertheless here, we developed a forecasting model based on oxidative stress to forecast the result of CRC survival and enhance clinical judgment. The training set was chosen from the transcriptomes of 177 CRC patients in GSE17536.
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