Prediction of Preeclampsia Using Machine Learning: A Systematic Review.

Preeclampsia is one of the leading causes of maternal and perinatal morbidity and mortality. Early prediction is the need of the hour so that interventions like aspirin prophylaxis can be started. Nowadays, machine learning (ML) is increasingly being used to predict the disease and its prognosis.

Transcatheter salvage of dying Glenn - An innovative strategy for postGlenn thrombosis.

PostGlenn thrombosis is an infrequent, serious complication requiring immediate attention, which is not uncommon in a resource-limited setting where patients are often lost to follow-up and have poor compliance with medications. This rare complication has infrequently been reported in the past. We describe a case of a massive thromboembolic event in a patient presenting acutely in a decompensated state 14 years after initial palliation by Glenn shunt.

Comparative evaluation of postoperative functional and esthetic outcomes for lip reconstruction with Fujimori gate flap versus Abbe-Estlander flap in patients being operated for oral squamous cell carcinoma.

Background: Lip carcinomas account for 23.6% to 30% of tumors affecting the oral cavity. Lip reconstruction aims to achieve a competent oral sphincter with a good cosmetic appearance while avoiding microstomia.

Enhancing prediction and inference of daily in-stream nutrient and sediment concentrations using an extreme gradient boosting based water quality estimation tool - XGBest.

Estimating constituent loads in streams and rivers is a crucial but challenging task due to low-frequency sampling in most watersheds. While predictive modeling can augment sparsely sampled water quality data, it can be challenging due to the complex and multifaceted interactions between several sub-watershed eco-hydrological processes. Traditional water quality prediction models, typically calibrated for individual sites, struggle to fully capture these interactions.