Sepsis

A deep learning approach to predicting hospitalized patients' SEIRD states using multimodal spatiotemporal data.

BACKGROUND AND OBJECTIVE: The increasing prevalence of hospital-acquired infections (HAIs) due to antimicrobial resistance presents a formidable challenge to patient outcomes and resource allocation. Existing prediction models often operate at a population level, failing to provide the granular, individual patient-specific risk assessments crucial for targeted interventions. Our study addresses th...

Development of an Explainable Machine Learning Model to Predict Mortality Risk in Sepsis Patients: Insights From a Real-World Clinical Data.

BACKGROUND: Sepsis is a life-threatening dysregulated host response to infection; early risk stratification is essential to guide intensive care. OBJECTIVE: To develop and interpret a machine learning model for predicting in-hospital mortality among intensive care unit (ICU) patients with sepsis. METHODS: We retrospectively analyzed clinical data from sepsis patients admitted to the ICU of the Fir...

Identification and Validation of Key Genes Related to Arginine Methylation Modification in Sepsis Using Transcriptome Combined with Mendelian Randomization Analysis.

BACKGROUND: Patients with sepsis often exhibit a decrease in lymphatic numbers, which can be facilitated by protein arginine methyltransferase (PRMT)....

Hybridized artificial intelligence system for reducing neonatal mortality in Nigeria.

BACKGROUND: Neonatal diseases represent the leading cause of death in Nigeria, ranking the country second globally in neonatal mortality rates. Early ...

Anxiety Promotes Occlusal Interference-Induced Myalgia via the Mesolimbic System.

Acute occlusal interference may induce chronic masticatory myalgia in some individuals. The potential factors and underlying mechanisms that predispos...

4-Hydroxy-2,5-dihydrothiazole derivatives as a new class of small-molecule antibiotics for MRSA: AI-integrated design, chemical synthesis and biological evaluation.

Staphylococcus aureus (S. aureus) is one of the most concerned Gram-positive bacteria due to its resistance to the commonly used antibiotics, methicil...

Hospital-acquired pneumonia: Past, present, and perspectives.

Hospital-acquired pneumonia (HAP) remains the most frequent and lethal hospital acquired infection, driving ICU mortality, prolonged length of stay, a...

Machine learning-enabled microfluidic ratiometric fluorescence sensor array based on lanthanide-gold nanoclusters for visual detection of multicomponent antibiotics.

The accumulation of multiple antibiotics in the environment poses severe threats to ecosystems and human health, demanding rapid, sensitive, and porta...

A rural-to-center artificial intelligence model for diagnosing Helicobacter pylori infection and premalignant gastric conditions using endoscopy images captured in routine practice.

Diagnosing Helicobacter pylori infection and premalignant gastric conditions typically requires 13C urea breath testing or histological assessment, wh...

Machine learning prediction of multidrug-resistant urinary tract infections in brain and spinal cord injury patients: a dual-center validation study.

BACKGROUND AND OBJECTIVE: Multidrug-resistant urinary tract infections (MDR UTIs) are a growing concern in patients with brain and spinal cord injurie...

Sysmex Cell Population Data for Diagnosing Infection in Patients With Suspected Sepsis in the Emergency Department.

OBJECTIVES: Early diagnosis of suspected sepsis is crucial to improve patient survival. Cell population (CP) data, a set of leucocyte research paramet...

Deep-learning-driven spectral image analysis for intelligent monitoring of multiple pesticides and antibiotics.

With the widespread use of pesticides and antibiotics in agriculture and healthcare, their associated environmental pollution and potential health haz...

Ahnak and Nckap1l as potential diagnostic biomarkers and therapeutic targets in Landiolol-mediated sepsis treatment.

PURPOSE: Landiolol is a beta-blocker used in the treatment of Sepsis. However, how this drug influences key genes and pathways involved in disease rem...

Multiplexed, rapid phenotypic antibiotic susceptibility testing based on angle-resolved light scattering imaging of microfluidic droplets.

INTRODUCTION: There is an urgent need for rapid, high-throughput phenotypic antimicrobial susceptibility testing (AST) capable of assessing a microbia...

Multidrug-resistant pathogens in UTIs: A concise review of epidemiology, diagnostics, and patent landscaping for precision healthcare.

UTIs are regarded as the second most prevalent global problem, with 150 to 250 million cases reported annually. Poor hygiene, anatomical abnormalities...

Deep learning-based cross-device standardization of surface-enhanced Raman spectroscopy for enhanced bacterial recognition.

Surface-enhanced Raman spectroscopy (SERS) is a powerful, label-free technique for pathogen detection; however, its broader adoption in clinical diagn...

Technical Feasibility of Quantitative Susceptibility Mapping Radiomics for Predicting Deep Brain Stimulation Outcomes in Parkinson Disease.

BACKGROUND AND OBJECTIVES: Parkinson disease (PD) patients with motor complications are often considered for deep brain stimulation (DBS) surgery. Pre...

Septic shock: Past, present, and perspectives.

Septic shock remains one of the most severe complications of infection, defined by circulatory, cellular, and metabolic dysfunction and associated wit...

Single Port Robot-Assisted Supraclavicular Flap Repair of Iatrogenic Hardware-Associated Pharyngeal Perforation: A Case Report.

BACKGROUND: The incidence of iatrogenic pharyngeal perforation has been reported to comprise 50%-75% of all pharyngeal perforations. In the context of...

Artificial intelligence and infectious diseases: tackling antimicrobial resistance, from personalised care to antibiotic discovery.

Antimicrobial resistance (AMR) is an intractable problem that has the potential to significantly limit advances in human health. Recently, the UN Gene...