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Abstract The application of Bayesian statistics in pivotal clinical trials has gained increasing attention, particularly for underpowered confirmatory trials such as those in pediatric and rare disease populations. Bayes...

Abstract Background Chronic conditions cause millions of deaths annually worldwide. Remote patient monitoring using wearable devices and sensors, combined with machine learning (ML), offers promising strategies for disea...

Abstract Background Adaptive designs (ADs) are increasingly used, whereby outcome data accumulated during the trial may inform a trial’s course in accordance with pre-specified rules at interim analyses. The benefits h...

Abstract Background Malaria continues to pose a major public health challenge in sub-Saharan Africa (SSA), where more than 95% of global cases and deaths occur. Despite WHO Global Technical Strategy for Malaria (GTS) tar...

Abstract Background Knee osteoarthritis (OA) is a leading global cause of disability, yet conventional tools lack sensitivity for early detection and precise prognostication. Artificial intelligence (AI) and machine lear...

Abstract Objective To accurately predict neurological outcomes among survivors after cardiac arrest (CA), we aim to analyze the experimental data of epileptiform electroencephalography (EEG) in CA survivors to explore th...

Abstract Background Nipple wounds are common complications during breastfeeding and may lead to pain, early cessation of breastfeeding, and maternal distress. Various pharmacological and non-pharmacological approaches ha...

Abstract Background Suicide attempts constitute a significant public health emergency, with Emergency Departments (EDs) serving as a primary point of contact for individuals in acute psychiatric crisis. This observationa...