Intensivists

Multi-modal Representations for Fine-grained Multi-label Critical View of Safety Recognition

The Critical View of Safety (CVS) is crucial for safe laparoscopic cholecystectomy, yet assessing CVS criteria remains a complex and challenging task, even for experts. Traditional models for CVS recognition depend on vision-only models learning with costly, labor-intensive spatial annotations. This study investigates how text can be harnessed as a powerful tool for both training and inference i...

M$^3$-Med: A Benchmark for Multi-lingual, Multi-modal, and Multi-hop Reasoning in Medical Instructional Video Understanding

With the rapid progress of artificial intelligence (AI) in multi-modal understanding, there is increasing potential for video comprehension technologies to support professional domains such as medical education. However, existing benchmarks suffer from two primary limitations: (1) Linguistic Singularity: they are largely confined to English, neglecting the need for multilingual resources; and (2...

BlowPrint: Blow-Based Multi-Factor Biometrics for Smartphone User Authentication

Biometric authentication is a widely used security mechanism that leverages unique physiological or behavioral characteristics to authenticate users...

Rapid diagnosis of lung cancer by multi-modal spectral data combined with deep learning.

Lung cancer is a malignant tumor that poses a serious threat to human health. Existing lung cancer diagnostic techniques face the challenges of high c...

Toward Edge General Intelligence with Multiple-Large Language Model (Multi-LLM): Architecture, Trust, and Orchestration

Edge computing enables real-time data processing closer to its source, thus improving the latency and performance of edge-enabled AI applications. H...

CHRONIC CRITICAL ILLNESS IN BONE TRAUMA PATIENTS: AN AI-BASED APPROACH FOR INTENSIVE CARE UNIT HEALTHCARE PROVIDERS.

Background: Chronic critical illness (CCI) is a serious condition characterized by a prolonged course of illness, resulting in elevated morbidity and ...

GLOBAL TRENDS IN ARTIFICIAL INTELLIGENCE AND SEPSIS-RELATED RESEARCH: A BIBLIOMETRIC ANALYSIS.

Background: In the field of bibliometrics, although some studies have conducted literature reviews and analyses on sepsis, these studies mainly focus ...

A systematic methodological evaluation of sepsis guidelines: Protocol for quality assessment and consistency of recommendations.

BACKGROUND: Sepsis is a leading cause of mortality worldwide, characterized by a dysregulated host response to infection. Despite the development of m...

Predictive modeling of ARDS mortality integrating biomarker/cytokine, clinical and metabolomic data.

Acute Respiratory Distress Syndrome (ARDS), characterized by the rapid onset of respiratory failure and mortality rates of ∼40%, remains a significant...

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 methods face challenges such as insufficient feature ...

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 the increasing demand for ICU resources and the n...

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 incomplete training data due to limitations in data collect...

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-ray imaging serving as the standard diagnostic mod...

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 successful with single serial manipulators. For multi-ar...

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

Identifying and measuring biases associated with sensitive attributes is a crucial consideration in healthcare to prevent treatment disparities. One...

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

The integration of artificial intelligence (AI) and machine learning-enabled medical technologies into clinical practice is expanding at an unpreceden...

Flow Diverse and Efficient: Learning Momentum Flow Matching via Stochastic Velocity Field Sampling

Recently, the rectified flow (RF) has emerged as the new state-of-the-art among flow-based diffusion models due to its high efficiency advantage in ...

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 through personalized, real-time decision-making i...

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 personalized medicine through improved diagnostics and...

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 architecture. The typical component of UNet famil...