Predicting Robotic Hysterectomy Incision Time: Optimizing Surgical Scheduling with Machine Learning.

Background And Objectives: Operating rooms (ORs) are critical for hospital revenue and cost management, with utilization efficiency directly affecting financial outcomes. Traditional surgical scheduling often results in suboptimal OR use. We aim to build a machine learning (ML) model to predict incision times for robotic-assisted hysterectomies, enhancing scheduling accuracy and hospital finances.

Ensemble priming via competitive inhibition: local mechanisms of sensory context storage and deviance detection in the neocortical column.

The process by which neocortical neurons and circuits amplify their response to an unexpected change in stimulus, often referred to as deviance detection (DD), has long been thought to be the product of specialized cell types and/or routing between mesoscopic brain areas. Here, we explore a different theory, whereby DD emerges from local network-level interactions within a neocortical column. We propose that deviance-driven neural dynamics can emerge through interactions between ensembles of neurons that have a fundamental inhibitory motif: competitive inhibition between reciprocally connected ensembles under modulation from feed-forward selective (dis)inhibition.

Perceptions and practices of imaging personnel and physicians regarding the use of brain MRI for dementia diagnosis in Uganda.

Introduction: Diagnosing dementia remains challenging in low-income settings due to limited diagnostic options and the absence of definitive biomarkers. The use of brain MRI in the diagnosis of dementia is infrequent in Uganda, and even when it is used, subtle findings like mild regional atrophy are often overlooked, despite being crucial for imaging diagnosis.

Objective: The purpose of this study was to explore the perceptions and practices of imaging personnel and physicians regarding the use of brain MRI as a diagnostic approach for dementia in Uganda.

Patient and public involvement in the design and protocol development for a platform randomised trial to evaluate diagnostic tests to optimise antimicrobial therapy (PROTECT).

Background: Our patient and public involvement activities were part of a project aiming to develop a master protocol and National Institute for Health and Care research application for the PROTECT trial aiming to assess the effectiveness, implementation, and efficiency of antimicrobial stewardship interventions, to safely reduce unnecessary antibiotic usage by excluding severe bacterial infection in acutely unwell patients.

Methods: Three public involvement sessions were held with representation from young people and parents, people from diverse backgrounds and people with experience of presenting to the emergency department with undifferentiated illness. The teleconference meetings lasted between 60-90 minutes, were recorded, notes were subsequently taken, and findings summarised.