Practical guide to building machine learning-based clinical prediction models using imbalanced datasets.

Clinical prediction models often aim to predict rare, high-risk events, but building such models requires robust understanding of imbalance datasets and their unique study design considerations. This practical guide highlights foundational prediction model principles for surgeon-data scientists and readers who encounter clinical prediction models, from feature engineering and algorithm selection strategies to model evaluation and design techniques specific to imbalanced datasets. We walk through a clinical example using readable code to highlight important considerations and common pitfalls in developing machine learning-based prediction models.

[STUDY OF DIRECT RESTORATION EFFICIENCY FOR ANTERIOR TEETH WITH VARIOUS PHOTOCOMPOSITE MATERIALS].

The aim of study was to evaluate the clinical efficiency of hard tissues restoration in frontal teeth with various photocomposite materials. The clinical study involved adult patients who needed the treatment of carious lesions of the frontal teeth or replacement of incompetent restorations. A nano-ceramic photocomposite was used in patients of group I, a microhybrid photocomposite in patients of group II, microfilled in patients in group III, and in patients in group IV - nanofilled photocomposite material.

Data-driven queries between medications and spontaneous preterm birth among 2.5 million pregnancies.

Background: Our goal was to develop an approach that can systematically identify potential associations between medication prescribed in pregnancy and spontaneous preterm birth (sPTB) by mining large administrative "claims" databases containing hundreds of medications. One such association that we illustrate emerged with antiviral medications used for herpes treatment.

Methods: IBM MarketScan® databases (2007-2016) were used.

Effect of Na adsorption on the structural and electronic properties of Si(111)√3 × √3-Au surface.

Adsorption of ∼0.1 ML of Na onto the Si(111)√3 × √3-Au surface held at 300 °C has been found to induce pronounced changes in its structural and electronic properties. Domain wall networks, characteristic of the pristine surface, are removed completely, leading to the formation of a highly ordered homogeneous surface.

[The influence of lactic acid bacteria and yeast on production of staphylococcal enterotoxins].

Research of influence of 10 lactic acid bacteria cultures on staphylococcal growth and production of staphylococcal enterotoxins SEA and SEB has shown that lactic acid bacteria slow down SEA in 5,7 fold and SEB - 1,56 fold. All investigated cultures possessed inhibition action on SEA and SEB production. Has been established, what lactic acid bacteria slow down growth of staphylococcus in 1,48 fold.