Development and validation of an artificial intelligence system for surgical case length prediction.

Background: Accurate case length estimation is a vital part of optimizing operating room use; however, significant inaccuracies exist with current solutions. The purpose of this study was to develop and validate an artificial intelligence system for improved surgical case length prediction by applying natural language processing and machine-learning methods.

Methods: All inpatient elective surgical cases longer than 30 minutes completed between 2017 and 2023 at a single, quaternary care hospital were considered.

Estimating the Prevalence of Child Abuse and Neglect Among Adolescents in Primary Care Through Diagnoses Codes and Free-Text EHR Clinical Notes.

Introduction: Adolescents' child abuse and neglect experiences are often under-documented in primary care, leading to missed opportunities for interventions. This study compares the prevalence of child abuse and neglect cases identified by diagnostic codes versus a natural language processing approach of clinical notes.

Method: We retrospectively analyzed data from 8,157 adolescents, using ICD-10 codes and a natural language processing algorithm to identify child abuse and neglect cases and applied topic modeling on clinical notes to extract prevalent topics.

Development of the Dissemination and Implementation Science Collaborative (DISC): Opportunities to enhance implementation science capacity among researchers and practitioners in South Carolina.

This paper explores the development of the Dissemination and Implementation Science Collaborative (DISC) at the Medical University of South Carolina, established through the Clinical and Translational Science Award program. DISC aims to accelerate clinical and translational science by providing training, mentorship, and collaboration opportunities in dissemination and implementation (D&I) science. Through DISC, investigators, trainees, and community partners are equipped with the knowledge and skills to conduct D&I research and translate findings into practice, particularly in South Carolina's public health and healthcare landscape.

Metropolitan-scale heralded entanglement of solid-state qubits.

A key challenge toward future quantum internet technology is connecting quantum processors at metropolitan scale. Here, we report on heralded entanglement between two independently operated quantum network nodes separated by 10 kilometers. The two nodes hosting diamond spin qubits are linked with a midpoint station via 25 kilometers of deployed optical fiber.

Health Risk Assessment of Heavy Metals in Lettuce and Spring Onion on Human Health in Kumasi, Ghana.

Introduction: The demand and consumption of vegetables are significantly increasing worldwide, which has resulted in urban farming on anthropogenic sites. This study assessed the concentrations of some selected heavy metals in lettuce and spring onion in line with the WHO/FAO required standard and its implications on human health.

Methods: The study was carried out in Kumasi, within moist semi-deciduous forest vegetation, Ghana.