Publications by authors named "Jin-Yeon Gil"
Article Synopsis
- Rheumatoid arthritis (RA) is a long-term inflammatory disease affecting joints, but treatment with TNF-α inhibitors has improved management, despite potential adverse skin reactions.
- A cohort study explored genetic risk factors for skin reactions induced by TNF-α inhibitors in RA patients using machine learning to analyze genetic data and develop a risk-scoring system.
- Key findings revealed that specific genetic markers significantly increased the likelihood of skin adverse events, with varying risk scores indicating a high correlation between score and incidence rates of skin complications, paving the way for personalized treatment approaches.
The primary objective of this study was to investigate the factors contributing to hyperglycemic adverse events (AEs) associated with the administration of remdesivir in hospitalized patients diagnosed with coronavirus disease 2019 (COVID-19). Furthermore, the study aimed to develop a risk score model employing various machine learning approaches. A total of 1262 patients were enrolled in this investigation.
View Article and Find Full Text PDFThis study was designed to investigate the effects of polymorphisms in RETN on remission in RA patients receiving TNF-α inhibitors. In addition, machine learning algorithms were trained to predict remission. Ten single-nucleotide polymorphisms were investigated.
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