Sepsis

Machine learning predicts sepsis deterioration trajectories.

Sepsis has heterogeneous clinical trajectories, but conventional severity scores offer only static r...

Impact of region-based shape alterations in MRI as indicators of Parkinson's Disease.

BACKGROUND: Parkinson's Disease (PD) is a neuro-degenerative condition that progressively impairs mo...

Personalized prediction of initial valproic acid dose in children with epilepsy using machine learning techniques.

INTRODUCTION: Valproic acid (VPA) is widely prescribed antiepileptic drug in children because of its...

Implantable microelectrode biosensors for monitoring neurometabolic markers.

Implantable microelectrode biosensors enable the monitoring of neurometabolic markers with high spat...

Metagenomic analysis of the gut microbiota in Cryptosporidium-infected Tibetan sheep.

Cryptosporidium are important causative parasitic protozoa that cause gastrointestinal discomfort an...

Improving severity grading of chemotherapy-induced myelosuppression in AML via data-driven and model-based deep learning.

Chemotherapy-induced myelosuppression in acute myeloid leukemia (AML) frequently leads to life-threa...

Antimicrobial discovery from underexplored environments: unlocking specialized metabolism.

The discovery of antibiotics transformed modern medicine and extended the average human lifespan by ...

Nanogels for the targeted delivery of antibiotic and antimicrobial drugs.

Nanoparticle-based drug delivery systems represent a promising platform for advancing biomedical the...

The Impact of Evaluation Strategy on Sepsis Prediction Model Performance Metrics in Intensive Care Data: Retrospective Cohort Study.

BACKGROUND: The prediction of the onset of sepsis, a life-threatening condition resulting from a dys...

Differential Factors Associated With the Presence of Persistent Symptoms in Individuals Diagnosed With Long COVID: Protocol for a Longitudinal Matched Case-Control Study.

BACKGROUND: Long COVID (postacute sequelae of SARS-CoV-2 infection) is a heterogeneous condition wit...

Integration of Systemic Immune-Inflammation Index and Lactate for diagnostic and early risk stratification in pediatric sepsis.

The role of digital tools and artificial intelligence in supporting antimicrobial stewardship: Study protocol for a systematic review.

INTRODUCTION: Since the post-antibiotic era, there has been significant difficulty in treating infec...

Linguistic, Orthographic, and Typographical Errors in Science (LOTS): A Growing Threat to Academic Integrity.

Biomedical engineers produce knowledge and artifacts. Across the life cycle of an idea, errors can c...

Identification and experimental validation of biomarkers associated with integrated stress response in sepsis.

BACKGROUND: Strategies that specifically target the integrated stress response (ISR) as a therapeuti...

Explainable Artificial Intelligence for Predicting Length of Stay and Treatment Response in Pediatric Asthma and Allergic Rhinitis: An Irregular Fuzzy Cellular Automata Approach Across Pre- and During-COVID-19 Periods.

OBJECTIVE: The COVID-19 pandemic significantly altered treatment strategies and healthcare utilizati...

Early-Stage Quality - Late-Stage Confidence: Neural Induction Quality Control as a Key to Reproducible MEA-based Neurotoxicity Assays.

Human induced pluripotent stem cell (hiPSC)-derived neural models combined with microelectrode array...

TCB-Kla: a hybrid deep learning model for predicting human lysine lactylation sites by incorporating transformer encoder and multi-scale CNN.

Lysine lactylation as a newly discovered post-translational modification of proteins, plays a key ro...

Systematic review of prediction models and meta-analysis of risk factors for invasive fungal infection in children.

OBJECTIVES: To review the application of prediction models and risk factors identified by prediction...

Machine learning prediction of positive urine cultures in an academic pediatric emergency department (ED).

BACKGROUND: Urinary tract infections (UTIs) are among the most common pediatric infections, but urin...

Integrating machine learning and artificial intelligence in the management of Acinetobacter infections: a narrative review.

Acinetobacter baumannii, particularly in its multidrug-resistant (MDR) and carbapenem-resistant (CRA...

Focusing on Data to Improve Machine Learning-Guided Antibiotic Discovery.

Machine learning (ML) is poised to accelerate antibiotic discovery by rapidly identifying and genera...