Synthetic Generation of Patient Service Utilization Data: A Scalability Study.

To address privacy and ethical issues in using health data for machine learning, we evaluate the scalability of advanced synthetic data generation methods like GANs, VAEs, copulaGAN, and transformer models specifically for patient service utilization data. Our study examines five models on data from a Canadian health authority, focusing on training and generation efficiency, data resemblance, and practical utility. Our findings indicate that statistical models excel in efficiency, while most models produce synthetic data that closely mirrors real data, and is also useful for real-world applications.

A Phase IIa Clinical Trial of 2-Iminobiotin for the Treatment of Birth Asphyxia in DR Congo, a Low-Income Country.

Aim: The main burden of hypoxic-ischemic encephalopathy falls in low-income countries. 2-Iminobiotin, a selective inhibitor of neuronal and inducible nitric oxide synthase, has been shown to be safe and effective in preclinical studies of birth asphyxia. Recently, safety and pharmacokinetics of 2-iminobiotin treatment on top of hypothermia has been described.

Observational study shows that it is feasible to provide neuroprotective treatment for neonatal encephalopathy in low-income countries.

Aim: Perinatal asphyxia is one of the most frequent causes of neonatal morbidity and mortality worldwide, and 96% of the burden of neonatal encephalopathy occurs in low-income countries. This study investigated the feasibility of providing neuroprotective treatment for neonatal encephalopathy in low-income countries.

Methods: Neonates with a gestational age of at least 36 weeks, with signs of perinatal asphyxia, were included in this 2015 observational study in three hospitals in Kinshasa, capital of the Democratic Republic of Congo.