Clinician and Visitor Activity Patterns in an Intensive Care Unit Room: A Study to Examine How Ambient Monitoring Can Inform the Measurement of Delirium Severity and Escalation of Care.

The early detection of the acute deterioration of escalating illness severity is crucial for effective patient management and can significantly impact patient outcomes. Ambient sensing technology, such as computer vision, may provide real-time information that could impact early recognition and response. This study aimed to develop a computer vision model to quantify the number and type (clinician vs.

The Wildlife Emerging Pathogens Initiative: Wild EPI and One Health.

One Health is an integrated approach that aims to balance and optimize the interconnectedness of the health of humans, animals, and ecosystems. Using this transdisciplinary approach, experts from across Canada led the formation of the Wildlife Emerging Pathogens Initiative (Wild EPI) to undertake research and surveillance programs evaluating the potential risks of emerging pathogens at the human-animal interface. Wild EPI is dedicated to implementing the One Health approach to enhance our understanding of the epidemiology and burden of zoonotic infections among humans and other animal hosts.

Applied Artificial Intelligence in Healthcare: A Review of Computer Vision Technology Application in Hospital Settings.

Computer vision (CV), a type of artificial intelligence (AI) that uses digital videos or a sequence of images to recognize content, has been used extensively across industries in recent years. However, in the healthcare industry, its applications are limited by factors like privacy, safety, and ethical concerns. Despite this, CV has the potential to improve patient monitoring, and system efficiencies, while reducing workload.

Centralized Multipatient Dashboards' Impact on Intensive Care Unit Clinician Performance and Satisfaction: A Systematic Review.

Background:  Intensive care unit (ICU) clinicians encounter frequent challenges with managing vast amounts of fragmented data while caring for multiple critically ill patients simultaneously. This may lead to increased provider cognitive load that may jeopardize patient safety.

Objectives:  This systematic review assesses the impact of centralized multipatient dashboards on ICU clinician performance, perceptions regarding the use of these tools, and patient outcomes.

Automatic ARDS surveillance with chest X-ray recognition using convolutional neural networks.

Objective: This study aims to design, validate and assess the accuracy a deep learning model capable of differentiation Chest X-Rays between pneumonia, acute respiratory distress syndrome (ARDS) and normal lungs.

Materials And Methods: A diagnostic performance study was conducted using Chest X-Ray images from adult patients admitted to a medical intensive care unit between January 2003 and November 2014. X-ray images from 15,899 patients were assigned one of three prespecified categories: "ARDS", "Pneumonia", or "Normal".

Evaluation of a Combined Live Attenuated Vaccine against Lumpy Skin Disease, Contagious Bovine Pleuropneumonia and Rift Valley Fever.

The use of effective vaccines is among the most important strategies for the prevention and progressive control of transboundary infectious animal diseases. However, the use of vaccine is often impeded by the cost, a lack of cold chains and other factors. In resource-limited countries in Africa, one approach to improve coverage and reduce cost is to vaccinate against multiple diseases using combined vaccines.

Characterising user engagement with mHealth for chronic disease self-management and impact on machine learning performance.

Mobile Health (mHealth) has the potential to be transformative in the management of chronic conditions. Machine learning can leverage self-reported data collected with apps to predict periods of increased health risk, alert users, and signpost interventions. Despite this, mHealth must balance the treatment burden of frequent self-reporting and predictive performance and safety.

Whole-genome sequencing of SARS-CoV-2 from the initial cases of domestic cat infections in Canada.

Two cat nasal swabs from Canada's earliest confirmed SARS-CoV-2 positive domestic cats were sequenced to over 99% SARS-CoV-2 genome coverage. One cat had lineage A.23.

Distinguishing host responses, extensive viral dissemination and long-term viral RNA persistence in domestic sheep experimentally infected with Crimean-Congo haemorrhagic fever virus Kosovo Hoti.

Crimean-Congo haemorrhagic fever orthonairovirus (CCHFV) is a tick-borne, risk group 4 pathogen that often causes a severe haemorrhagic disease in humans (CCHF) with high case fatality rates. The virus is believed to be maintained in a tick-vertebrate-tick ecological cycle involving numerous wild and domestic animal species; however the biology of CCHFV infection in these animals remains poorly understood. Here, we experimentally infect domestic sheep with CCHFV Kosovo Hoti, a clinical isolate representing high pathogenicity to humans and increasingly utilized in current research.

Domestic pigs are susceptible to experimental infection with non-human primate-derived Reston virus without the need for adaptation.

Domestic pigs are a critical component of the food supply and one of the most commonly raised production animals. Pork consumption has driven the intensification of pig production expanding into environments conducive to increased emergence and spread of infectious diseases, including the spillover of pathogens into human populations. One of these emerging viruses, Reston virus (RESTV), is an enigma among the Orthoebolavirus genus in that its lack of human pathogenicity is in stark contrast to the high virulence associated with most other ebolaviruses.

Impact of SARS-CoV-2 Vaccine Rollout on Hispanic and Non-Hispanic Admission and Mortality Trends: An Interrupted Time Series Analysis.

Background: Challenges with SARS-CoV-2 vaccine prioritization, access, and hesitancy have influenced vaccination uptake.

Research Question: Was the impact of SARS-CoV-2 vaccine rollout on COVID-19 monthly admission and mortality trends different between Hispanic and non-Hispanic populations?

Study Design And Methods: We used interrupted time series analysis to conduct an ancillary study of the Viral Infection and Respiratory Illness Universal Study registry supplemented by electronic health record data from five participating Mayo Clinic sites in Florida, Arizona, Minnesota, and Wisconsin. We included hospitalized patients with COVID-19 admitted between April 2020 and December 2021.

Healer's Perspective: A Course for Medical Students.

Introduction: Healer's Perspective was a course on Zoom developed from the Sanford Summer Leadership Academy. The five, one-hour sessions were held during the fall of 2022 and was student-led. Thirty-seven students from the Sanford School of Medicine class of 2025 participated in this course.

mA governs length-dependent enrichment of mRNAs in stress granules.

Stress granules are biomolecular condensates composed of protein and mRNA. One feature of stress granule-enriched mRNAs is that they are often longer than average. Another feature of stress granule-enriched mRNAs is that they often contain multiple N-methyladenosine (mA) residues.

Henipavirus zoonosis: outbreaks, animal hosts and potential new emergence.

Hendra virus (HeV) and Nipah virus (NiV) are biosafety level 4 zoonotic pathogens causing severe and often fatal neurological and respiratory disease. These agents have been recognized by the World Health Organization as top priority pathogens expected to result in severe future outbreaks. HeV has caused sporadic infections in horses and a small number of human cases in Australia since 1994.

Predicting sepsis onset using a machine learned causal probabilistic network algorithm based on electronic health records data.

Sepsis is a leading cause of mortality and early identification improves survival. With increasing digitalization of health care data automated sepsis prediction models hold promise to aid in prompt recognition. Most previous studies have focused on the intensive care unit (ICU) setting.

Estimating vaccine coverage in conflict settings using geospatial methods: a case study in Borno state, Nigeria.

Reliable estimates of subnational vaccination coverage are critical to track progress towards global immunisation targets and ensure equitable health outcomes for all children. However, conflict can limit the reliability of coverage estimates from traditional household-based surveys due to an inability to sample in unsafe and insecure areas and increased uncertainty in underlying population estimates. In these situations, model-based geostatistical (MBG) approaches offer alternative coverage estimates for administrative units affected by conflict.

Strategies to Improve Multi-enzyme Compatibility and Coordination in One-Pot SHERLOCK.

While molecular diagnostics generally require heating elements that supply high temperatures such as 95 °C in polymerase chain reaction and 60-69 °C in loop-mediated isothermal amplification, the recently developed CRISPR-based SHERLOCK (specific high-sensitivity enzymatic reporter unlocking) platform can operate at 37 °C or a similar ambient temperature. This unique advantage may be translated into highly energy-efficient or equipment-free molecular diagnostic systems with unrestricted deployability. SHERLOCK is characterized by ultra-high sensitivity when performed in a traditional two-step format.