Hospital-Based Medicine

Intensivists

Latest AI and machine learning research in intensivists for healthcare professionals.

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Showing 1177-1197 of 4,973 articles
MHS U-Net: Multi-scale hybrid subtraction network for medical image segmentation.

Medical image segmentation plays a critical role in modern clinical diagnosis. However, existing met...

Jul 2025 40435671
A comprehensive review of ICU readmission prediction models: From statistical methods to deep learning approaches.

The prediction of Intensive Care Unit (ICU) readmission has become a crucial area of research due to...

Jul 2025 40300338
Task-augmented cross-view imputation network for partial multi-view incomplete multi-label classification.

In real-world scenarios, multi-view multi-label learning often encounters the challenge of incomplet...

Jul 2025 40088833
BPD-Neo: An MRI Dataset for Lung-Trachea Segmentation with Clinical Data for Neonatal Bronchopulmonary Dysplasia

Bronchopulmonary dysplasia (BPD) is a common complication among preterm neonates, with portable X-...

IKDiffuser: Fast and Diverse Inverse Kinematics Solution Generation for Multi-arm Robotic Systems

Solving Inverse Kinematics (IK) problems is fundamental to robotics, but has primarily been succes...

Path-specific effects for pulse-oximetry guided decisions in critical care

Identifying and measuring biases associated with sensitive attributes is a crucial consideration i...

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

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

Jun 2025 40506762
SAFER: A Calibrated Risk-Aware Multimodal Recommendation Model for Dynamic Treatment Regimes

Dynamic treatment regimes (DTRs) are critical to precision medicine, optimizing long-term outcomes...

ICU-TSB: A Benchmark for Temporal Patient Representation Learning for Unsupervised Stratification into Patient Cohorts

Patient stratification identifying clinically meaningful subgroups is essential for advancing pers...

FuseUNet: A Multi-Scale Feature Fusion Method for U-like Networks

Medical image segmentation is a critical task in computer vision, with UNet serving as a milestone...

Predicting ICU In-Hospital Mortality Using Adaptive Transformer Layer Fusion

Early identification of high-risk ICU patients is crucial for directing limited medical resources....

Evaluating MLLMs with Multimodal Multi-image Reasoning Benchmark

With enhanced capabilities and widespread applications, Multimodal Large Language Models (MLLMs) a...

MIND: Material Interface Generation from UDFs for Non-Manifold Surface Reconstruction

Unsigned distance fields (UDFs) are widely used in 3D deep learning due to their ability to repres...

Predicting Postoperative Stroke in Elderly SICU Patients: An Interpretable Machine Learning Model Using MIMIC Data

Postoperative stroke remains a critical complication in elderly surgical intensive care unit (SICU...

EarthMind: Towards Multi-Granular and Multi-Sensor Earth Observation with Large Multimodal Models

Large Multimodal Models (LMMs) have demonstrated strong performance in various vision-language tas...

Cluster discharge resonance neuron model and its application in machinery multi-dimensional fault vibration signals.

Through the analysis of multidimensional vibration signals of machinery, existing faults in mechanic...

Jun 2025 40492844
Development and External Validation of a Detection Model to Retrospectively Identify Patients With Acute Respiratory Distress Syndrome.

OBJECTIVE: The aim of this study was to develop and externally validate a machine-learning model tha...

Jun 2025 40197621
MEF-Net: Multi-scale and edge feature fusion network for intracranial hemorrhage segmentation in CT images.

Intracranial Hemorrhage (ICH) refers to cerebral bleeding resulting from ruptured blood vessels with...

Jun 2025 40286496
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...

Jun 2025 40466050
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...

Jun 2025 40443788
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