Publications by authors named "Taegyu Um"
Checkpoint inhibitor-associated pneumonitis (CIP) after immunotherapy has become a challenging issue in non-small cell lung cancer (NSCLC) patients. This study leverages artificial intelligence (AI) algorithms to analyze radiomic features, aiming to predict the occurrence of CIP, as well as tumor response. This study analyzed data from 159 stage III-IV NSCLC patients undergoing immunotherapy.
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- * Data from the Korea National Health and Nutrition Examination Survey (KNHANES) was used, categorizing participants into adherent, non-adherent, and non-treatment groups, with a large majority being adherent.
- * Findings indicate that older age, longer duration of hypertension, diabetes, and ischemic heart disease are linked to better adherence, highlighting the need for tailored health interventions for those with hypertension in Korea.