Intensivists

Data Integration with Fusion Searchlight: Classifying Brain States from Resting-state fMRI

Resting-state fMRI captures spontaneous neural activity characterized by complex spatiotemporal dynamics. Various metrics, such as local and global brain connectivity and low-frequency amplitude fluctuations, quantify distinct aspects of these dynamics. However, these measures are typically analyzed independently, overlooking their interrelations and potentially limiting analytical sensitivity. ...

Hero-SR: One-Step Diffusion for Super-Resolution with Human Perception Priors

Owing to the robust priors of diffusion models, recent approaches have shown promise in addressing real-world super-resolution (Real-SR). However, achieving semantic consistency and perceptual naturalness to meet human perception demands remains difficult, especially under conditions of heavy degradation and varied input complexities. To tackle this, we propose Hero-SR, a one-step diffusion-base...

Thermal Image-based Fault Diagnosis in Induction Machines via Self-Organized Operational Neural Networks

Condition monitoring of induction machines is crucial to prevent costly interruptions and equipment failure. Mechanical faults such as misalignment ...

Multi-Party Supervised Fine-tuning of Language Models for Multi-Party Dialogue Generation

Large Language Models (LLM) are usually fine-tuned to participate in dyadic or two-party dialogues, which can not adapt well to multi-party dialogue...

AI-driven Inverse Design of Band-Tunable Mechanical Metastructures for Tailored Vibration Mitigation

On-demand vibration mitigation in a mechanical system needs the suitable design of multiscale metastructures, involving complex unit cells. In this ...

Sharp-It: A Multi-view to Multi-view Diffusion Model for 3D Synthesis and Manipulation

Advancements in text-to-image diffusion models have led to significant progress in fast 3D content creation. One common approach is to generate a se...

MCBLT: Multi-Camera Multi-Object 3D Tracking in Long Videos

Object perception from multi-view cameras is crucial for intelligent systems, particularly in indoor environments, e.g., warehouses, retail stores, ...

Building a Risk Scoring Model for ARDS in Lung Adenocarcinoma Patients Using Machine Learning Algorithms.

Lung adenocarcinoma (LUAD), the predominant form of non-small-cell lung cancer, is frequently complicated by acute respiratory distress syndrome (ARDS...

Artificial Intelligence-Driven Precision Medicine: Multi-Omics and Spatial Multi-Omics Approaches in Diffuse Large B-Cell Lymphoma (DLBCL).

In this comprehensive review, we delve into the transformative role of artificial intelligence (AI) in refining the application of multi-omics and spa...

Enhancing Glucose Level Prediction of ICU Patients through Hierarchical Modeling of Irregular Time-Series

Accurately predicting blood glucose (BG) levels of ICU patients is critical, as both hypoglycemia (BG < 70 mg/dL) and hyperglycemia (BG > 180 mg/dL)...

Off-Policy Selection for Initiating Human-Centric Experimental Design

In human-centric tasks such as healthcare and education, the heterogeneity among patients and students necessitates personalized treatments and inst...

MixEHR-Nest: Identifying Subphenotypes within Electronic Health Records through Hierarchical Guided-Topic Modeling

Automatic subphenotyping from electronic health records (EHRs)provides numerous opportunities to understand diseases with unique subgroups and enhan...

Recent Progress in the Physical Principles of Dynamic Ground Self-Righting.

Animals and robots must self-right on the ground after overturning. Biology research has described various strategies and motor patterns in many speci...

Unveiling the glycolysis in sepsis: Integrated bioinformatics and machine learning analysis identifies crucial roles for IER3, DSC2, and PPARG in disease pathogenesis.

Sepsis, a multifaceted syndrome driven by an imbalanced host response to infection, remains a significant medical challenge. At its core lies the pivo...

Multi-scale Multi-instance Visual Sound Localization and Segmentation

Visual sound localization is a typical and challenging problem that predicts the location of objects corresponding to the sound source in a video. P...

A Comparative Analysis of Federated and Centralized Learning for SpO2 Prediction in Five Critical Care Databases.

This study explores the potential of federated learning (FL) to develop a predictive model of hypoxemia in intensive care unit (ICU) patients. Central...

Optimizing ICU Care: Machine Learning and PCA for Early Prediction of Renal Replacement Therapy Requirement.

Forecasting the need for Renal Replacement Therapy (RRT) in intensive care units (ICUs) at an early stage can enhance patient outcomes and optimize re...

Development and Validation of an Interpretable Machine Learning Model for Early Prognosis Prediction in ICU Patients with Malignant Tumors and Hyperkalemia.

This study aims to develop and validate a machine learning (ML) predictive model for assessing mortality in patients with malignant tumors and hyperka...

SepsisLab: Early Sepsis Prediction with Uncertainty Quantification and Active Sensing

Sepsis is the leading cause of in-hospital mortality in the USA. Early sepsis onset prediction and diagnosis could significantly improve the surviva...

Machine Learning-Based Prediction Models of Mortality for Intensive Care Unit Patients Using Nursing Records.

This study aimed to develop ICU mortality prediction models using a conceptual framework, focusing on nurses' concerns reflected in nursing records fr...