Critical Care

Enhancing cryo-EM structure prediction with DeepTracer and AlphaFold2 integration.

Understanding the protein structures is invaluable in various biomedical applications, such as vaccine development. Protein structure model building from experimental electron density maps is a time-consuming and labor-intensive task. To address the challenge, machine learning approaches have been proposed to automate this process. Currently, the majority of the experimental maps in the database l...

Automatically pre-screening patients for the rare disease aromatic l-amino acid decarboxylase deficiency using knowledge engineering, natural language processing, and machine learning on a large EHR population.

OBJECTIVES: Electronic health record (EHR) data may facilitate the identification of rare diseases in patients, such as aromatic l-amino acid decarboxylase deficiency (AADCd), an autosomal recessive disease caused by pathogenic variants in the dopa decarboxylase gene. Deficiency of the AADC enzyme results in combined severe reductions in monoamine neurotransmitters: dopamine, serotonin, epinephrin...

Treatment Prediction in the ICU Using a Partitioned, Sequential, Deep Time Series Analysis.

We have developed a time-oriented machine-learning tool to predict the binary decision of administering a medication and the quantitative decision reg...

Large Language Model Symptom Identification from Clinical Text: A Multi-Center Study

Recognition of patient symptoms is core to medicine, research, and public health. We tested four large language models (LLMs) identifying 11 symptoms ...

Neural Granger Causal Discovery for Derangements in ICU-Acquired Acute Kidney Injury Patients.

Nowadays, healthcare systems increasingly utilize automated surveillance of electronic medical record (EMR) data to detect adverse events with specifi...

Better Blood Pressure Control for Stroke Patients in the ICU: A Deep Reinforcement Learning with Supervised Guidance Approach for Adaptive Infusion Rate Tuning.

Blood pressure variability (BPV) plays a critical role in vascular diseases, particularly in acute ischemic stroke patients in intensive care units (I...

Where do doctors disagree? Characterizing Decision Points for Safe Reinforcement Learning in Choosing Vasopressor Treatment.

In clinical settings, domain experts sometimes disagree on optimal treatment actions. These "decision points" must be comprehensively characterized, a...

Pentagon Found Daily, Metagenomic Detection of Novel Bioaerosol Threats to Be Cost-Prohibitive: Can Virtualization and AI Make It Cost-Effective?

In 2022, the Pentagon Force Protection Agency found threat agnostic detection of novel bioaerosol threats to be "not feasible for daily operations" du...

Airway leakage due to malpositioning of esophageal temperature probe during robot-assisted radical prostatectomy: a case report.

Measuring patients' core body temperature during surgery is essential and commonly performed with an esophageal temperature probe. The probe must be p...

Overview of artificial intelligence in point-of-care ultrasound. New horizons for respiratory system diagnoses.

Throughout the past decades ultrasonography did not prove to be a procedure of choice if regarded as part of the routine bedside examination. The reas...

Understanding the Manufacturing Process of Lipid Nanoparticles for mRNA Delivery Using Machine Learning.

Lipid nanoparticles (LNPs), used for mRNA vaccines against severe acute respiratory syndrome coronavirus 2, protect mRNA and deliver it into cells, ma...

Multi-Modal Sleep Stage Classification With Two-Stream Encoder-Decoder.

Sleep staging serves as a fundamental assessment for sleep quality measurement and sleep disorder diagnosis. Although current deep learning approaches...

Diagnostic performance of machine-learning algorithms for sepsis prediction: An updated meta-analysis.

BACKGROUND: Early identification of sepsis has been shown to significantly improve patient prognosis.

CvTMorph: Improving Local Feature Extraction in Medical Image Registration for Respiratory Motion Modeling with Convolutional Vision Transformer.

BACKGROUND: Accurately modeling respiratory motion in medical images is crucial for various applications, including radiation therapy planning. Howeve...

Interpretable Machine Learning Approach for Predicting 30-Day Mortality of Critical Ill Patients with Pulmonary Embolism and Heart Failure: A Retrospective Study.

BACKGROUND: Pulmonary embolism (PE) patients combined with heart failure (HF) have been reported to have a high short-term mortality. However, few stu...

Drive Pressure-Guided Individualized Positive End-Expiratory Pressure in Traumatic Brain Injury Surgery: A Randomized Controlled Trial.

AIM: Intraoperative lung-protective ventilation strategies (LPVS) have been shown to improve lung oxygenation and prevent postoperative pulmonary prob...

Antihypertensive prescribing patterns in non-dialysis dependent chronic kidney disease: Findings from the Salford Kidney Study.

BACKGROUND: Hypertension is commonly observed in patients living with chronic kidney disease (CKD). Finding an optimal treatment regime remains challe...

Identification of Elderly Patients with Lower Respiratory Tract Infection by Artificial Intelligence Analysis of Cough Pattern Sounds.

BACKGROUND: Automatic recognition of cough sounds shows promise in the diagnosis of respiratory conditions. This study investigated the diagnostic val...

[Intelligent rehabilitation platform in intensive care unit].

As the development of rehabilitation medicine and critical care medicine, intensive care rehabilitation has become the focus of attention. With the de...

ExpertNet: A Deep Learning Approach to Combined Risk Modeling and Subtyping in Intensive Care Units.

Risk models play a crucial role in disease prevention, particularly in intensive care units (ICUs). Diseases often have complex manifestations with he...