Critical Care

Latest AI and machine learning research in critical care for healthcare professionals.

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Subcategories: Sepsis
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Primer on large language models: an educational overview for intensivists.

The integration of artificial intelligence (AI) and machine learning-enabled medical technologies in...

[Acoustic technology empowers the diagnosis and treatment of respiratory diseases: challenges, and prospects].

Respiratory diseases is a major challenge to global public health. In recent years, acoustic technol...

Exploring nanoparticles in lungs under COPD conditions for nanospray drug flow and deposition: CFD simulations and AI predictions.

Chronic obstructive pulmonary disease (COPD) plays a heavy burden on individuals and the social heal...

Multimodal CustOmics: A unified and interpretable multi-task deep learning framework for multimodal integrative data analysis in oncology.

Characterizing cancer presents a delicate challenge as it involves deciphering complex biological in...

Development of Machine-Learning-Based Models for Detection of Cognitive Impairment in Patients Receiving Maintenance Hemodialysis.

BACKGROUND: Cognitive impairment is common but frequently undiagnosed in the dialysis population. We...

Multi-Objective Evolutionary Optimization Boosted Deep Neural Networks for Few-Shot Medical Segmentation With Noisy Labels.

Fully-supervised deep neural networks have achieved remarkable progress in medical image segmentatio...

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 imp...

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, v...

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, v...

Diagnostic Stewardship of Blood Cultures in the Pediatric ICU Using Machine Learning.

OBJECTIVE: The medical community recently experienced a severe shortage of blood culture media bottl...

Predicted and Explained: Transforming drug discovery with AI for high-precision receptor-ligand interaction modeling and binding analysis.

The pharmaceutical industry faces persistent challenges in developing effective treatments for compl...

GRU4ACE: Enhancing ACE inhibitory peptide prediction by integrating gated recurrent unit with multi-source feature embeddings.

Accurate identification of angiotensin-I-converting enzyme (ACE) inhibitory peptides is essential fo...

Predicting blood pressure without a cuff using a unique multi-modal wearable device and machine learning algorithm.

Blood pressure is a critical risk factor for cardiovascular diseases (CVDs), yet most adults do not ...

Rapid identification of coffee species and origin using affordable multi-channel spectral sensor combined with machine learning.

The rapid identification of coffee species and origin is critical for ensuring quality control and a...

Attention to early stages: predicting acute kidney injury in a post cardiosurgical ICU setting using an inclusive time-to-event model.

BACKGROUND: Acute kidney injury (AKI) is a critical complication in intensive care units (ICUs) that...

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...

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