Publications by authors named "J E Korte"
Article Synopsis
- This study analyzed trends in prepregnancy obesity and gestational weight gain in South Carolina, focusing on racial and ethnic differences during and before the COVID-19 pandemic.
- The research utilized hospital discharge codes and birth certificates from 306,344 full-term births, employing statistical models to assess weight gain adequacy and prepregnancy obesity risks.
- Findings showed an increase in inadequate weight gain across all groups before the pandemic, a stabilization during it, and a rise in prepregnancy obesity primarily among women of "other" races, with no overall changes for Hispanic, Black, and White women.
Article Synopsis
- * Elevated CO levels, nutrients, and temperatures lead to harmful algal blooms (HABs), which can negatively impact water quality, ecosystems, and public health due to the production of toxins.
- * The review discusses the dual role of algal blooms in carbon fixation and their complex metabolites, highlights advancements in understanding these structures, and examines strategies for managing and controlling HABs.
Background: The conventional lying down position for radiation therapy can be challenging for patients due to pain, swallowing or breathing issues. To provide an alternative upright treatment position for these patients, we have developed a portable rotating radiation therapy platform which integrates with conventional photon treatment machines. The device enables cone-beam computed tomography (CBCT) imaging of patients in an upright position, and the future delivery of therapeutic radiation.
View Article and Find Full Text PDFPrediction of Thrombus Formation within an Oxygenator via Bioimpedance Analysis.
Biosensors (Basel)
October 2024
Blood clot formation inside the membrane oxygenator (MO) remains a risk in extracorporeal membrane oxygenation (ECMO). It is associated with thromboembolic complications and normally detectable only at an advanced stage. Established clinical monitoring techniques lack predictive capabilities, emphasizing the need for refinement in MO monitoring towards an early warning system.
View Article and Find Full Text PDFArticle Synopsis
- Identifying high-risk areas for infectious diseases is crucial for effective public health responses, and this paper introduces a new prediction metric using a Bayesian spatio-temporal model.
- The metric enhances current techniques by combining three key factors: the risk profile of an area, the trend of risk over time, and the influence of neighboring regions, all weighted appropriately for better accuracy.
- Through simulations, the study confirms that local risk and neighborhood effects significantly enhance sensitivity, while trend analysis improves the specificity and overall predictive accuracy of risk assessments, evidenced by its application to COVID-19 data in South Carolina.