Sepsis

Differentiating Treatment-Resistant Depression With and Without Parkinsonism in the Elderly From a Psychiatric Perspective by Tc-TRODAT-1 SPECT Imaging.

OBJECTIVES: Late-life depression often overlaps with neurodegenerative diseases leading to diagnostic and treatment challenges for neuropsychiatrists. This study aimed to differentiate elderly treatment-resistant depression (TRD) comorbid with parkinsonism from elderly TRD without Parkinsonism as well as elderly healthy controls using striatum dopamine transporter (DAT) imaging by Tc TRODAT-1 SPEC...

The MEFIER Score-A Risk Score to Stratify Infective Endocarditis in Patients With Bacteremia Based on an 11-Year Territory-Wide Cohort.

BACKGROUND: The 2023 Duke-International Society for Cardiovascular Infectious Diseases (ISCVID) guideline included as a typical infective endocarditis (IE) organism irrespective of the primary source and setting of infection. Universal echocardiogram for bacteremia is resource-intensive. Our aim was to develop a risk score that can be applied at the time of bacteremia.

Use of an Untrained Large Language Model for Antibiotic Prescription in Pediatric Infectious Diseases at Primary Care Settings: A Study From the Italian Society for Pediatric Infectious Diseases.

The development of artificial intelligence systems is revolutionizing many fields of medicine, but specific studies are still missing in pediatrics. I...

The best machine learning algorithm for building surgical site infection predictive models: A systematic review and network meta-analysis.

BACKGROUND: Many machine learning (ML) algorithms have been used to develop surgical site infection (SSI) prediction models, but little is known about...

Artificial Intelligence and Hand Hygiene Accuracy: A New Era in Infection Control for Dental Practices.

OBJECTIVE: The study aimed to assess the efficacy of an artificial intelligence (AI) model in evaluating hand hygiene (HH) performance compared to inf...

Machine Learning Insights Into Amputation Risk: Evaluating Wound Classification Systems in Diabetic Foot Ulcers.

This study compares the performance of various wound classification systems to determine which system most effectively predicts amputation risk in dia...

Quantifying Healthcare Provider Perceptions of a Novel Deep Learning Algorithm to Predict Sepsis: Electronic Survey.

IMPORTANCE: Sepsis is a major cause of morbidity and mortality, with early intervention shown to improve outcomes. Predictive modeling and artificial ...

Machine Learning Accurately Predicts Need for Critical Care Support in Patients Admitted to Hospital for Community-Acquired Pneumonia.

OBJECTIVES: Hospitalized community-acquired pneumonia (CAP) patients are admitted for ventilation, vasopressors, and renal replacement therapy (RRT). ...

Machine Learning Accurately Predicts Need for Critical Care Support in Patients Admitted to Hospital for Community-Acquired Pneumonia.

OBJECTIVES: Hospitalized community-acquired pneumonia (CAP) patients are admitted for ventilation, vasopressors, and renal replacement therapy (RRT). ...

Reinforcement learning using neural networks in estimating an optimal dynamic treatment regime in patients with sepsis.

OBJECTIVE: Early fluid resuscitation is crucial in the treatment of sepsis, yet the optimal dosage remains debated. This study aims to determine the o...

Computational screening of natural products as tryptophan 2,3-dioxygenase inhibitors: Insights from CNN-based QSAR, molecular docking, ADMET, and molecular dynamics simulations.

Parkinson's disease (PD) is characterised by a complex array of motor, psychiatric, and gastrointestinal symptoms, many of which are linked to disrupt...

Prognostic value of the Glucose-to-Albumin ratio in sepsis-related mortality: A retrospective ICU study.

AIMS: To investigate the prognostic value of the glucose-to-albumin ratio (GAR) in predicting 30-day and 90-day mortality in septic ICU patients.

Intelligent Prediction Platform for Sepsis Risk Based on Real-Time Dynamic Temporal Features: Design Study.

BACKGROUND: The development of sepsis in the intensive care unit (ICU) is rapid, the golden rescue time is short, and the effective way to reduce mort...

Harnessing AI to revolutionize photocatalytic degradation of Tetracycline via optimized UV/ZrO/NaOCl reaction pathways.

This paper assesses the presentation of Gradient Boosting Regression (GBR), Ridge Regression (RR), and Particle Swarm Optimization (PSO) models in imp...

Development and Validation of SXI++ LNM Algorithm for Sepsis Prediction

Sepsis is a life-threatening condition affecting over 48.9 million people globally and causing 11 million deaths annually. Despite medical advanceme...

Scalable and robust machine learning framework for HIV classification using clinical and laboratory data.

Human Immunodeficiency Virus (HIV) is a retrovirus that weakens the immune system, increasing vulnerability to infections and cancers. HIV spreads pri...

Learning optimal treatment strategies for intraoperative hypotension using deep reinforcement learning

Traditional methods of surgical decision making heavily rely on human experience and prompt actions, which are variable. A data-driven system genera...

A machine learning and centrifugal microfluidics platform for bedside prediction of sepsis.

Sepsis is a life-threatening organ dysfunction due to a dysfunctional response to infection. Delays in diagnosis have substantial impact on survival. ...

MedDreamer: Model-Based Reinforcement Learning with Latent Imagination on Complex EHRs for Clinical Decision Support

Timely and personalized treatment decisions are essential across a wide range of healthcare settings where patient responses vary significantly and ...

Predicting the risk of ibrutinib in combination with R-ICE in patients with relapsed or refractory DLBCL using explainable machine learning algorithms.

Relapsed or refractory diffuse large B-cell lymphoma (DLBCL) poses significant therapeutic challenges due to heterogeneous patient outcomes. This stud...