Critical Care

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

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Enhancing mechanical ventilator reliability through machine learning based predictive maintenance.

BackgroundWith the advancement of Artificial Intelligence (AI), clinical engineering has witnessed t...

May 2025 40331554
Learning Multi-view Multi-class Anomaly Detection

The latest trend in anomaly detection is to train a unified model instead of training a separate m...

Pediatric Asthma Detection with Googles HeAR Model: An AI-Driven Respiratory Sound Classifier

Early detection of asthma in children is crucial to prevent long-term respiratory complications an...

Model uncertainty quantification using feature confidence sets for outcome excursions

When implementing prediction models for high-stakes real-world applications such as medicine, fina...

(1)
Assessing the Utility of Audio Foundation Models for Heart and Respiratory Sound Analysis

Pre-trained deep learning models, known as foundation models, have become essential building block...

Early Detection of Multidrug Resistance Using Multivariate Time Series Analysis and Interpretable Patient-Similarity Representations

Background and Objectives: Multidrug Resistance (MDR) is a critical global health issue, causing i...

(1)
ExOSITO: Explainable Off-Policy Learning with Side Information for Intensive Care Unit Blood Test Orders

Ordering a minimal subset of lab tests for patients in the intensive care unit (ICU) can be challe...

Waveform-Logmel Audio Neural Networks for Respiratory Sound Classification

Auscultatory analysis using an electronic stethoscope has attracted increasing attention in the cl...

(2)
Balancing Fairness and Performance in Healthcare AI: A Gradient Reconciliation Approach

The rapid growth of healthcare data and advances in computational power have accelerated the adopt...

EarthGPT-X: Enabling MLLMs to Flexibly and Comprehensively Understand Multi-Source Remote Sensing Imagery

Recent advances in the visual-language area have developed natural multi-modal large language mode...

(3)
Predictive Multiplicity in Survival Models: A Method for Quantifying Model Uncertainty in Predictive Maintenance Applications

In many applications, especially those involving prediction, models may yield near-optimal perform...

Respiratory Inhaler Sound Event Classification Using Self-Supervised Learning

Asthma is a chronic respiratory condition that affects millions of people worldwide. While this co...

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Enhancing Multi-task Learning Capability of Medical Generalist Foundation Model via Image-centric Multi-annotation Data

The emergence of medical generalist foundation models has revolutionized conventional task-specifi...

CUT: Pruning Pre-Trained Multi-Task Models into Compact Models for Edge Devices

Multi-task learning has garnered widespread attention in the industry due to its efficient data ut...

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The Structural Safety Generalization Problem

LLM jailbreaks are a widespread safety challenge. Given this problem has not yet been tractable, w...

Reconstructing Sepsis Trajectories from Clinical Case Reports using LLMs: the Textual Time Series Corpus for Sepsis

Clinical case reports and discharge summaries may be the most complete and accurate summarization ...

(2)
Inferring Outcome Means of Exponential Family Distributions Estimated by Deep Neural Networks

While deep neural networks (DNNs) are widely used for prediction, inference on DNN-estimated subje...

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