Development and validation of artificial intelligence models for early detection of postoperative infections (PERISCOPE): a multicentre study using electronic health record data.

Background: Postoperative infections significantly impact patient outcomes and costs, exacerbated by late diagnoses, yet early reliable predictors are scarce. Existing artificial intelligence (AI) models for postoperative infection prediction often lack external validation or perform poorly in local settings when validated. We aimed to develop locally valid models as part of the PERISCOPE AI system to enable early detection, safer discharge, and more timely treatment of patients.

Robotic Versus Laparoscopic Liver Resection: A Nationwide Propensity Score Matched Analysis.

Objective: To compare nationwide outcomes of robotic liver resection (RLR) with laparoscopic liver resection (LLR).

Background: Minimally invasive liver resection is increasingly performed using the robotic approach as this could help overcome inherent technical limitations of laparoscopy. It is unknown if this translates to improved patient outcomes.

A systematic narrative review of the involvement of executive functions in flying performance of pilots.

Piloting is a complex task that demands robust cognitive functions to handle multiple tasks simultaneously in a constantly changing environment. As a result, cognitive abilities, particularly executive functions (EFs), have gained significant importance in relation to flight performance. However, the specific EFs most critical for predicting flight performance remain unclear.

Exploring Different Sampling Strategies: A Description of Our Success in Reaching Hard-to-Reach Turkish and Moroccan Immigrant Women in The Netherlands.

Introduction: In the Netherlands, since 1996, there is a national cervical cancer (CC) screening programme in place for women aged 30-60 years. The participation of Turkish- and Moroccan-Dutch women is very low. To facilitate their informed decision-making, we developed a culturally sensitive educational video, and evaluated it through a questionnaire study.

Enhancing Standardized and Structured Recording by Elderly Care Physicians for Reusing Electronic Health Record Data: Interview Study.

Background: Elderly care physicians (ECPs) in nursing homes document patients' health, medical conditions, and the care provided in electronic health records (EHRs). However, much of these health data currently lack structure and standardization, limiting their potential for health information exchange across care providers and reuse for quality improvement, policy development, and scientific research. Enhancing this potential requires insight into the attitudes and behaviors of ECPs toward standardized and structured recording in EHRs.