首页|Affiliated Cancer Hospital Reports Findings in Machine Learning (Non-invasive Pr ediction of Lymph Node Metastasis in NSCLC Using Clinical, Radiomics, and Deep L earning Features From 18FFDG PET/CT Based on Interpretable Machine Learning)
Affiliated Cancer Hospital Reports Findings in Machine Learning (Non-invasive Pr ediction of Lymph Node Metastasis in NSCLC Using Clinical, Radiomics, and Deep L earning Features From 18FFDG PET/CT Based on Interpretable Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning is th e subject of a report. According to newsoriginating from Harbin, People’s Repub lic of China, by NewsRx correspondents, research stated, “Thisstudy aimed to de velop and evaluate a machine learning model combining clinical, radiomics, and d eeplearning features derived from PET/CT imaging to predict lymph node metastas is (LNM) in patients withnon-small cell lung cancer (NSCLC). The model’s interp retability was enhanced using Shapley additiveexplanations (SHAP).”
HarbinPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesHealth and MedicineHemic and Immune SystemsImmunologyLymph NodesLymphoidTissueMachine Learning
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