Handling missing data in variational autoencoder based item response theory.

Recently Variational Autoencoders (VAEs) have been proposed as a method to estimate high dimensional Item Response Theory (IRT) models on large datasets. Although these improve the efficiency of estimation drastically compared to traditional methods, they have no natural way to deal with missing values. In this paper, we adapt three existing methods from the VAE literature to the IRT setting and propose one new method.

The Importance of Patient Systemic Health Status in High-Grade Chondrosarcoma Prognosis: A National Multicenter Study.

Due to the relatively advanced age and high mortality rate of patients with high-grade chondrosarcoma (CS), it is important to holistically assess patient- and tumor characteristics in multidisciplinary team and shared decision-making with regard to treatment options. While current prognostic models include multiple tumor and treatment characteristics, the only patient characteristics that are commonly included are age and gender. Based on clinical experience, we believe that factors related to patient preoperative systemic health status such as the American Society of Anesthesiologists (ASA) score may be equally important prognostic factors for overall survival (OS).

Optimized methods for measuring competitive binding of chemical substances to thyroid hormone distributor proteins transthyretin and thyroxine binding globulin.

Transthyretin (TTR) and thyroxine-binding globulin (TBG) are two major thyroid hormone (TH) distributor proteins in human plasma, playing important roles in stabilizing the TH levels in plasma, delivery of TH to target tissues, and trans-barrier transport. Binding of xenobiotics to these distributor proteins can potentially affect all these three important roles of distributor proteins. Therefore, fast and cost-effective experimental methods are required for both TTR and TBG to screen both existing and new chemicals for their potential binding.

From everyday life to measurable problematic smartphone use: The development and validation of the Smartphone Use Problems Identification Questionnaire (SUPIQ).

Background And Aims: Problematic smartphone use (PSU) has gained attention, but its definition remains debated. This study aimed to develop and validate a new scale measuring PSU-the Smartphone Use Problems Identification Questionnaire (SUPIQ).

Methods: Using two separate samples, a university community sample (N = 292) and a general population sample (N = 397), we investigated: (1) the construct validity of the SUPIQ through exploratory and confirmatory factor analyses; (2) the convergent validity of the SUPIQ with correlation analyses and the visualized partial correlation network analyses; (3) the psychometric equivalence of the SUPIQ across two samples through multigroup confirmatory factor analyses; (4) the explanatory power of the SUPIQ over the Short Version of Smartphone Addiction Scale (SAS-SV) with hierarchical multiple regressions.