-A machine learning model to predict surgical site infection after surgery of lower extremity fractures.

Purpose: This study aimed to develop machine learning algorithms for identifying predictive factors associated with the risk of postoperative surgical site infection in patients with lower extremity fractures.

Methods: A machine learning analysis was conducted on a dataset comprising 1,579 patients who underwent surgical fixation for lower extremity fractures to create a predictive model for risk stratification of postoperative surgical site infection. We evaluated different clinical and demographic variables to train four machine learning models (neural networks, boosted generalised linear model, naïve bayes, and penalised discriminant analysis).

Precision Medicine with 3D Ultrasound.

Introduction: A 56-year-old woman was referred for thyroid nodules (TNs) found on a carotid ultrasonography (US). Her laboratories showed a normal thyroid stimulation hormone of 1.530 µIU/mL, normal thyroid hormone levels, and her thyroid antibodies were not elevated.

Impact of COVID-19 on people with asthma: a mixed methods analysis from a UK wide survey.

Introduction: The impact of acute COVID-19 on people with asthma appears complex, being moderated by multiple interacting disease-specific, demographic and environmental factors. Research regarding longer-term effects in this group is limited. We aimed to assess impacts of COVID-19 and predictors of persistent symptoms, in people with asthma.

External Load and Muscle Activation Monitoring of NCAA Division I Basketball Team Using Smart Compression Shorts.

There is scarce research into the use of Strive Sense3 smart compression shorts to measure external load with accelerometry and muscle load (i.e., muscle activations) with surface electromyography in basketball.