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Full-Text Articles in Medicine and Health Sciences
Dysregulation Of Dna Methylation And Epigenetic Clocks In Prostate Cancer Among Puerto Rican Men, Anders Berglund, Jaime Matta, Jarline Encarnación-Medina, Carmen Ortiz-Sanchéz, Julie Dutil, Raymond Linares, Joshua Marcial, Caren Abreu-Takemura, Natasha Moreno, Ryan Putney, Ratna Chakrabarti, Hui Yi Lin, Kosj Yamoah, Carlos Diaz Osterman, Liang Wang, Jasreman Dhillon, Youngchul Kim, Seung Joon Kim, Gilberto Ruiz-Deya, Jong Y. Park
Dysregulation Of Dna Methylation And Epigenetic Clocks In Prostate Cancer Among Puerto Rican Men, Anders Berglund, Jaime Matta, Jarline Encarnación-Medina, Carmen Ortiz-Sanchéz, Julie Dutil, Raymond Linares, Joshua Marcial, Caren Abreu-Takemura, Natasha Moreno, Ryan Putney, Ratna Chakrabarti, Hui Yi Lin, Kosj Yamoah, Carlos Diaz Osterman, Liang Wang, Jasreman Dhillon, Youngchul Kim, Seung Joon Kim, Gilberto Ruiz-Deya, Jong Y. Park
School of Public Health Faculty Publications
In 2021, approximately 248,530 new prostate cancer (PCa) cases are estimated in the United States. Hispanic/Latinos (H/L) are the second largest racial/ethnic group in the US. The objective of this study was to assess DNA methylation patterns between aggressive and indolent PCa along with ancestry proportions in 49 H/L men from Puerto Rico (PR). Prostate tumors were classified as aggressive (n = 17) and indolent (n = 32) based on the Gleason score. Genomic DNA samples were extracted by macro-dissection. DNA methylation patterns were assessed using the Illumina EPIC DNA methylation platform. We used ADMIXTURE to estimate global ancestry proportions. …
Class Imbalance In Out-Of-Distribution Datasets: Improving The Robustness Of The Textcnn For The Classification Of Rare Cancer Types, Kevin De Angeli, Shang Gao, Ioana Danciu, Eric B. Durbin, Xiao Cheng Wu, Antoinette Stroup, Jennifer Doherty, Stephen Schwartz, Charles Wiggins, Mark Damesyn, Linda Coyle, Lynne Penberthy, Georgia D. Tourassi, Hong Jun Yoon
Class Imbalance In Out-Of-Distribution Datasets: Improving The Robustness Of The Textcnn For The Classification Of Rare Cancer Types, Kevin De Angeli, Shang Gao, Ioana Danciu, Eric B. Durbin, Xiao Cheng Wu, Antoinette Stroup, Jennifer Doherty, Stephen Schwartz, Charles Wiggins, Mark Damesyn, Linda Coyle, Lynne Penberthy, Georgia D. Tourassi, Hong Jun Yoon
School of Public Health Faculty Publications
In the last decade, the widespread adoption of electronic health record documentation has created huge opportunities for information mining. Natural language processing (NLP) techniques using machine and deep learning are becoming increasingly widespread for information extraction tasks from unstructured clinical notes. Disparities in performance when deploying machine learning models in the real world have recently received considerable attention. In the clinical NLP domain, the robustness of convolutional neural networks (CNNs) for classifying cancer pathology reports under natural distribution shifts remains understudied. In this research, we aim to quantify and improve the performance of the CNN for text classification on out-of-distribution …
The Role Of Education On Cancer Amenable Mortality Among Non-Hispanic Blacks &Amp; Non-Hispanic Whites In The United States (1989–2018), Alberto Barcelo, Linda Duffett-Leger, Maria Pastor-Valero, Juliana Pereira, Fernando A.B. Colugnati, Edward Trapido
The Role Of Education On Cancer Amenable Mortality Among Non-Hispanic Blacks &Amp; Non-Hispanic Whites In The United States (1989–2018), Alberto Barcelo, Linda Duffett-Leger, Maria Pastor-Valero, Juliana Pereira, Fernando A.B. Colugnati, Edward Trapido
School of Public Health Faculty Publications
Background: Cancer mortality in the U.S. has fallen in recent decades; however, individuals with lower levels of education experienced a smaller decline than more highly educated individuals. This analysis aimed to measure the influence of education lower than a high school diploma, on cancer amenable mortality among Non-Hispanic Whites (NHW) and Non-Hispanic Blacks (NHB) in the U.S. from 1989 to 2018. Methods: We analyzed data from 8.2 million death certificates of men and women who died from cancer between 1989 and 2018. We examined 5-year and calendar period intervals, as well as annual percent changes (APC). APC was adjusted for …