Critical Care

Micro-expression recognition based on multi-scale 3D residual convolutional neural network.

In demanding application scenarios such as clinical psychotherapy and criminal interrogation, the ac...

Artificial Intelligence in Pediatric Respiratory Diseases: Current Status and Future Promises.

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 i...

Comprehensive exploration of multi-modal and multi-branch imaging markers for autism diagnosis and interpretation: insights from an advanced deep learning model.

Autism spectrum disorder is a complex neurodevelopmental condition with diverse genetic and brain in...

MSPA-DLA++: A Multi-Scale Phase Attention Deep Layer Aggregation for Lesion Detection in Multi-Phase CT Images.

Object detection using convolutional neural networks (CNNs) has achieved high performance and achiev...

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 administer...

Temporomandibular Joint Disorders Multi-Class Classification Using Deep Learning.

Temporomandibular joint (TMJ) disorders have been misinterpreted by various normal TMJ features lead...

scMMT: a multi-use deep learning approach for cell annotation, protein prediction and embedding in single-cell RNA-seq data.

Accurate cell type annotation in single-cell RNA-sequencing data is essential for advancing biologic...

AgeAnnoMO: a knowledgebase of multi-omics annotation for animal aging.

Aging entails gradual functional decline influenced by interconnected factors. Multiple hallmarks pr...

Enhancing Antibiotic Stewardship: A Machine Learning Approach to Predicting Antibiotic Resistance in Inpatient Care.

Antibiotics have been crucial in advancing medical treatments, but the growing threat of antibiotic ...

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 "decisio...

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 i...

A Multi-Task Learning Approach for Segmentation of Breast Arterial Calcifications in Screening Mammograms.

Screening mammogram is a standard and cost-efficient imaging procedure to measure breast cancer risk...

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

Nowadays, healthcare systems increasingly utilize automated surveillance of electronic medical recor...

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 ox...

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 ...

Can AI generate diagnostic reports for radiologist approval on CXR images? A multi-reader and multi-case observer performance study.

BACKGROUND: Accurately detecting a variety of lung abnormalities from heterogenous chest X-ray (CXR)...

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 applicat...

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...

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

Sleep staging serves as a fundamental assessment for sleep quality measurement and sleep disorder di...

Machine learning-based prediction of cerebral oxygen saturation based on multi-modal cerebral oximetry data.

This study develops machine learning-based algorithms that facilitate accurate prediction of cerebra...