Forward geometric model prediction of a 6-RSU parallel manipulator using a modified NARX Bayesian neural network.

The precision and safety of robotic applications rely on accurate robot models. Bayesian Neural Networks (BNNs) offer the capability to acquire intricate models and provide insights into inherent uncertainties. While recent studies have successfully employed machine learning to predict the Forward Geometric Model (FGM) of a 6-DOF (degrees of freedom) parallel manipulator, traditional methods lack predictive uncertainty estimation.

Soft Tissue Facial Changes Following Massive Weight Loss Secondary to Medical and Surgical Bariatric Interventions: A Systematic Review.

Bariatric interventions, both surgical and medical, are increasingly employed by patients to achieve weight reduction and enhance overall health. However, there is growing concern about the associated changes in soft tissue facial aesthetics resulting from these interventions. In this systematic review, the authors aimed to analyze the existing literature regarding soft tissue facial changes after bariatric interventions, with a focus on the influence of massive weight loss on facial aging, attractiveness, and considerations for facial rejuvenation.

Impact of Hypoglycemia on Hospitalized Patients With Hepatocellular Carcinoma.

Aims Hepatocellular carcinoma (HCC) is one of the common liver malignancies that presents a challenge to global healthcare. The impact and outcomes of hypoglycemia in HCC have not been studied in detail before. This study aimed to investigate the outcomes and prognosis associated with hypoglycemia in patients diagnosed with HCC, utilizing a large-scale database approach.

Personalized insulin dosing using reinforcement learning for high-fat meals and aerobic exercises in type 1 diabetes: a proof-of-concept trial.

In type 1 diabetes, high-fat meals require more insulin to prevent hyperglycemia while meals followed by aerobic exercises require less insulin to prevent hypoglycemia, but the adjustments needed vary between individuals. We propose a decision support system with reinforcement learning to personalize insulin doses for high-fat meals and postprandial aerobic exercises. We test this system in a single-arm 16-week study in 15 adults on multiple daily injections therapy (NCT05041621).