Critical Care

AI Hiring with LLMs: A Context-Aware and Explainable Multi-Agent Framework for Resume Screening

Resume screening is a critical yet time-intensive process in talent acquisition, requiring recruiters to analyze vast volume of job applications while remaining objective, accurate, and fair. With the advancements in Large Language Models (LLMs), their reasoning capabilities and extensive knowledge bases demonstrate new opportunities to streamline and automate recruitment workflows. In this work...

Audio-based digital biomarkers in diagnosing and managing respiratory diseases: a systematic review and bibliometric analysis.

Advances in wearable sensors and artificial intelligence have greatly enhanced the potential of digitised audio biomarkers for disease diagnostics and monitoring. In respiratory care, evidence supporting their clinical use remains fragmented and inconclusive. This study aimed to assess the current research landscape of digital audio biomarkers in respiratory medicine through a bibliometric analysi...

Fast and interpretable mortality risk scores for critical care patients.

OBJECTIVE: Prediction of mortality in intensive care unit (ICU) patients typically relies on black box models (that are unacceptable for use in hospit...

An Explainable Neural Radiomic Sequence Model with Spatiotemporal Continuity for Quantifying 4DCT-based Pulmonary Ventilation

Accurate evaluation of regional lung ventilation is essential for the management and treatment of lung cancer patients, supporting assessments of pu...

Thinking Longer, Not Larger: Enhancing Software Engineering Agents via Scaling Test-Time Compute

Recent advancements in software engineering agents have demonstrated promising capabilities in automating program improvements. However, their relia...

MGD-SAM2: Multi-view Guided Detail-enhanced Segment Anything Model 2 for High-Resolution Class-agnostic Segmentation

Segment Anything Models (SAMs), as vision foundation models, have demonstrated remarkable performance across various image analysis tasks. Despite t...

Multi-label classification for multi-temporal, multi-spatial coral reef condition monitoring using vision foundation model with adapter learning

Coral reef ecosystems provide essential ecosystem services, but face significant threats from climate change and human activities. Although advances...

Graph Kolmogorov-Arnold Networks for Multi-Cancer Classification and Biomarker Identification, An Interpretable Multi-Omics Approach

The integration of heterogeneous multi-omics datasets at a systems level remains a central challenge for developing analytical and computational mod...

DynaGraph: Interpretable Multi-Label Prediction from EHRs via Dynamic Graph Learning and Contrastive Augmentation

Learning from longitudinal electronic health records is limited if it does not capture the temporal trajectories of the patient's state in a clinica...

X$^{2}$-Gaussian: 4D Radiative Gaussian Splatting for Continuous-time Tomographic Reconstruction

Four-dimensional computed tomography (4D CT) reconstruction is crucial for capturing dynamic anatomical changes but faces inherent limitations from ...

Sparse Bayesian Learning for Label Efficiency in Cardiac Real-Time MRI

Cardiac real-time magnetic resonance imaging (MRI) is an emerging technology that images the heart at up to 50 frames per second, offering insight i...

3MDBench: Medical Multimodal Multi-agent Dialogue Benchmark

Large Vision-Language Models (LVLMs) are increasingly being explored for applications in telemedicine, yet their ability to engage with diverse pati...

TAMA: A Human-AI Collaborative Thematic Analysis Framework Using Multi-Agent LLMs for Clinical Interviews

Thematic analysis (TA) is a widely used qualitative approach for uncovering latent meanings in unstructured text data. TA provides valuable insights...

MMGen: Unified Multi-modal Image Generation and Understanding in One Go

A unified diffusion framework for multi-modal generation and understanding has the transformative potential to achieve seamless and controllable ima...

Reinforcing Clinical Decision Support through Multi-Agent Systems and Ethical AI Governance

Recent advances in the data-driven medicine approach, which integrates ethically managed and explainable artificial intelligence into clinical decis...

Unpaired Translation of Chest X-ray Images for Lung Opacity Diagnosis via Adaptive Activation Masks and Cross-Domain Alignment

Chest X-ray radiographs (CXRs) play a pivotal role in diagnosing and monitoring cardiopulmonary diseases. However, lung opacities in CXRs frequently...

Multi-agent Application System in Office Collaboration Scenarios

This paper introduces a multi-agent application system designed to enhance office collaboration efficiency and work quality. The system integrates a...

BIMII-Net: Brain-Inspired Multi-Iterative Interactive Network for RGB-T Road Scene Semantic Segmentation

RGB-T road scene semantic segmentation enhances visual scene understanding in complex environments characterized by inadequate illumination or occlu...

PHEONA: An Evaluation Framework for Large Language Model-based Approaches to Computational Phenotyping

Computational phenotyping is essential for biomedical research but often requires significant time and resources, especially since traditional metho...

RomanTex: Decoupling 3D-aware Rotary Positional Embedded Multi-Attention Network for Texture Synthesis

Painting textures for existing geometries is a critical yet labor-intensive process in 3D asset generation. Recent advancements in text-to-image (T2...