Yinying Chai
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SHAP-interpretable machine learning integrating exposures and multi-omics reveals immune alterations and biomarkers in COPD–lung cancer comorbidity
Abstract Introduction: Chronic obstructive pulmonary disease (COPD) and lung cancer (LC) frequently co-occur and share environmental and biological determinants, yet their cross-scale associations remain incompletely understood. Artificial intelligence and machine learning–based integration of exposome and multi-omics data provide new opportunities for dissecting this complex comorbidity.
Mediating Role of Depression in the Association Between the Body Roundness Index and Female Infertility: A Cross-Sectional Study Using Data From the National Health and Nutrition Examination Survey (NHANES) 2013–2018
Conflicts of Interest The authors declare no conflicts of interest. Data Availability Statement The data that support the findings of this study are available in National Health and Nutrition Examination Survey (NHANES) at http://www.cdc.gov/nchs/nhanes/. These data were derived from the following resources available in the public domain: National Health and Nutrition Examination Survey (NHANES), http://www.cdc.gov/nchs/nhanes/.
Regarding: association of aspirin use alone with mortality and liver-related events in MASLD: a multi-institutional three-year study
We have read with great interest the recent article by Huang et al. investigating the association of aspirin use with clinical outcomes in patients with metabolic dysfunction-associated steatotic liver disease (MASLD) [Citation1]. The authors present a valuable retrospective analysis offering important insights into aspirin’s potential role in MASLD management.
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