Sepsis

Dense sampling of choices links high learning rates to obesity and low reward sensitivity to binge eating

Mounting evidence shows that obesity is associated with alterations in dopamine transmission. However, in humans, corresponding changes in dopamine-dependent behavior, such as reward learning with increasing BMI, have not been conclusively established and dissociated from pathological eating behavior. Here, we provide a principled assessment of differences in reinforcement learning (RL) related to...

Outbreak and Postnatal Antibiotic Exposures Drive the Development Trajectory of the Nasopharyngeal Microbiota in the First Year of Life

Early exposure to antibiotics and prolonged hospitalization in preterm infants may perturb microbiome development and contribute to adverse health outcomes. Although nasopharyngeal microbiomes are linked to respiratory infections, their early development is underexplored and often assessed with 16S rRNA sequencing, which lacks species resolution. Here, we investigated nasopharyngeal microbiota dyn...

AI Implementation in U.S. Healthcare and Its Association With Elder Mortality and Quality of Care

Hospitals are increasingly adopting artificial intelligence (AI) tools in clinical care. However, their overall impact on the health of older adults r...

COVID-19 modulates pregnancy outcomes

The COVID-19 pandemic exposed many pregnant individuals to SARS-CoV-2. Literature suggests a link between gestational COVID-19 and adverse gestational...

Machine Learning-Based Identification of Sickle Cell Disease Subphenotypes in Clinical Trial Data

Sickle Cell Disease (SCD) is a rare autosomal recessive disorder caused by a point mutation producing abnormal hemoglobin S, leading to deformed red b...

Urinary collagen peptides predict mortality

Organ fibrosis caused by the presence of excessive extracellular matrix (ECM) is strongly related to mortality. Urinary peptide signatures were report...

Diagnostic accuracy of a high-throughput multiplex immunoassay for the detection of Mpox virus infection and MVA-BN vaccination up to two years after exposure

Mpox, caused by mpox virus (MPXV), has gained global attention following the 2022 Clade IIb outbreak and the emergence of two novel Clade I lineages i...

Nucleotide motif-guided selection of plasma microRNA biomarkers for organ injury prediction in trauma

Trauma remains a leading cause of morbidity and mortality in part due to secondary organ injury and infection. Yet, our ability to predict the downstr...

Advancing the Safe Motherhood Initiative: a qualitative and sentiment analysis of local physician’s perspectives on antibiotic self-medication during pregnancy in a low- and middle-income country

Although the Safe Motherhood Initiative is currently a global priority, the implications of maternal self-medication for meeting Safe Motherhood and S...

Evaluation of a real time machine learning sepsis risk algorithm for Emergency Department waiting rooms (SAFE-WAIT)

To evaluate and compare the real-time Sepsis risk Artificial intelligence algorithm For Emergency department WAITing room (SAFE-WAIT) model with the s...

Prediction of impulse control disorders in Parkinson’s disease: a longitudinal machine learning study

Impulse control disorders (ICD) in Parkinson’s disease (PD) patients mainly occur as adverse effects of dopamine replacement therapy. Despite several ...

A Hybrid AutoML Ensemble Integrating Conventional Learners and Gradient-Boosting Models for Multi-Outcome Prediction in ICU Patients with Pseudomonas aeruginosa

Carbapenem resistance in Pseudomonas aeruginosa is increasing in intensive care units (ICUs). To enhance antimicrobial stewardship and infection contr...

Leveraging Machine Learning for Developing and Validating a Neonatal Acute Kidney Injury Prediction Model (NEPHRO): A Comprehensive Evidence-Based Neonatal AKI Risk Stratification Tool

Acute kidney injury (AKI) is a serious and common complication among critically ill neonates. Preventing or treating AKI early requires timely predict...

CLIF-Net: Intersection-guided Cross-view Fusion Network for Infection Detection from Cranial Ultrasound

This paper addresses the problem of detecting possible serious bacterial infection (pSBI) of infancy, i.e. a clinical presentation consistent with bac...

Case-Control Matching Erodes Feature Discriminability for AI-driven Sepsis Prediction in ICUs: A Retrospective Cohort Study

Sepsis remains a leading cause of intensive care unit (ICU) mortality worldwide, and early detection is essential for improving survival through timel...

Development of a pilot machine learning model to predict successful cure in critically ill patients with community-acquired pneumonia

Severe community-acquired pneumonia (CAP) remains a major cause of critical illness, yet there are no validated early clinical criteria to predict sho...

Incidence of Long COVID Following Reinfection with COVID-19

COVID-19 reinfections have emerged as a critical concern, particularly in relation to post-acute sequelae of SARS-CoV-2 infection, commonly known as l...

Development and Validation of VC-MAES and VC-SEPS: Deep Learning-Based Early Warning Systems for Hospitalized Patients

The timely detection of ward deterioration—including unplanned intensive care unit (ICU) transfer, cardiac arrest, death, and sepsis—remains an unmet ...

Predicting Tuberculosis Incidence in Adult HIV Patients on ART in Debre Markos, Ethiopia: A Machine Learning Approach

Tuberculosis (TB) is the commonest comorbidity among individuals with HIV/AIDS, especially in low- and middle-income nations such as Ethiopia. Early d...

Human breast cancer is linked to Epstein-Barr virus because it targets stem cells: bioinformatic chromosome correlations

Breast cancer originates from rare “cancer stem cells”. Stem cells are especially susceptible to becoming cancerous because they readily become differ...