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Item type:Publication, Disparities in mortality among HER2-positive breast cancer patients treated with trastuzumab in Chile (2015–2024): real-world evidence from 4,920 cases(Informa UK Limited, 2026-07-01); - Some of the metrics are blocked by yourconsent settings
Item type:Product, Dataset - Hantavirus cardiopulmonary syndrome: organ support requirements and outcomes from a national Chilean cohort(FONASA, 2026); ; - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Hantavirus cardiopulmonary syndrome: organ support requirements and outcomes from a national Chilean cohort(Springer Science and Business Media LLC, 2026-06-25); ; 1 - Some of the metrics are blocked by yourconsent settings
Item type:Product, Dataset - Multimorbidity profile among cancer-related hospitalization events in younger and older patients: a large-scale nationwide cross-sectional study(GITHUB, 2026); ; - Some of the metrics are blocked by yourconsent settings
Item type:Product, Dataset - Integration of RNA Editing into Multiomics Machine Learning Models for Predicting Drug Responses in Breast Cancer Patients(GITHUB, 2026); ; 1 - Some of the metrics are blocked by yourconsent settings
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Item type:Publication, 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Integration of RNA Editing into Multiomics Machine Learning Models for Predicting Drug Responses in Breast Cancer Patients(MDPI AG, 2026-03-14); ; Background: The integration of multi-omics data, such as genomics and transcriptomics, into artificial intelligence models has advanced precision medicine. However, their clinical applicability remains limited due to model complexity. We integrated DNA mutation, RNA expression, and A>I(G) RNA editing data to develop a predictive model for drug response in breast cancer. Methods: We analyzed 104 patients from the Breast Cancer Genome-Guided Therapy Study (ClinicalTrials.gov: NCT02022202). Clinical variables, gene expression, tumor and germline DNA variants, and RNA editing features were integrated into machine learning models to predict therapy response. Generalized linear models (GLM), random forest (RF), and support vector machines (SVM) were trained and evaluated across multiple random 70/30 train-test splits. Feature selection was performed exclusively within the training set using LASSO regularization. Model performance was assessed using the F1-score on independent test sets. The additive effect of RNA editing was evaluated using paired comparisons across identical train/test splits. Results: We characterized the cohort using clinical, mutational, transcriptomic, and RNA editing profiles in 69 non-responders and 35 responders. Across repeated splits, adding RNA editing frequently maintained or modestly improved predictive performance, particularly in expression-based models, with paired analyses showing a statistically significant increase in F1-score. Conclusions: RNA editing represents a complementary molecular layer that can enhance multi-omic models for therapy response prediction in breast cancer, supporting further investigation of epitranscriptomic features in precision oncology.5 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Mapping within-country disparities in Ischemic stroke burden and trends by human development index, age and sex(Elsevier BV, 2026-05); ; Craig S. Anderson1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Poverty and ethnic patterns in COVID-19 excess mortality: evidence from Chile, 2020-2022(Oxford University Press (OUP), 2025-12-10); ; Elienai Joaquin-DamasThe COVID-19 pandemic highlighted deep-rooted health inequities globally, with marginalized populations showing disproportionate disease burden. We employed Serfling regression models and multivariable analyses to estimate excess mortality across geographic, demographic, and poverty groups from 2020 to 2022 in Chile. Elderly populations (80+ years) experienced the highest excess mortality (267.35 per 10 000 population), more than 8 times higher than those under 80 years (30.80 per 10 000 population). Multivariable linear regression models showed both Indigenous proportion (coefficient = 53.66, P &lt; .001) and elderly population proportion (coefficient = 5.68, P &lt; .01) as the strong predictors of comuna level excess mortality. Poverty correlated significantly with excess mortality (r = 0.23, P &lt; .001) but this association weakened after adjustment for other covariates in multivariable models. Excess mortality peaked in 2021 rather than in 2020 for most groups, with males initially experiencing higher rates during early pandemic waves. Spatial analyses revealed statistically significant clustering (Moran’s I = 0.119, P &lt; .001) with identifiable hotspots in northern Chile and parts of the south. These findings indicated persistent mortality disparities by age and Indigenous status, independent of poverty, and highlight the urgent need for equity-focused pandemic preparedness. An effective pandemic response should integrate biomedical measures, such as vaccination, with culturally grounded strategies that address structural barriers and the broader social determinants of health.</jats:p>1