This paper presents a methodology for automatically extracting insights from PubMed articles using a Natural Language Processing (NLP) framework. Our approach, leveraging advanced NLP techniques and Named Entity Recognition (NER), is crucial for advancing pharmacogenomics and other scientific fields that benefit from streamlined access to literature through automated services like RESTful APIs.Building a new NLP model presents several challenges.
View Article and Find Full Text PDFBackground: The correct understanding of the epidemiological dynamics of COVID-19, caused by the SARS-CoV-2, is essential for formulating public policies of disease containment.
Methods: In this study, we constructed a picture of the epidemiological dynamics of COVID-19 in a Brazilian population of almost 17000 patients in 15 months. We specifically studied the fluctuations of COVID-19 cases and deaths due to COVID-19 over time according to host gender, age, viral load, and genetic variants.