Critical Care

Text mining for case report articles on "peritoneal dialysis" from PubMed database.

INTRODUCTION: The number of published medical articles on peritoneal dialysis (PD) has been increasing, and efficiently selecting information from numerous articles can be difficult. In this study, we examined whether artificial intelligence (AI) text mining can be a good support for efficiently collecting PD information.

Utilizing semantically enhanced self-supervised graph convolution and multi-head attention fusion for herb recommendation.

Traditional Chinese herbal medicine has long been recognized as an effective natural therapy. Recently, the development of recommendation systems for herbs has garnered widespread academic attention, as these systems significantly impact the application of traditional Chinese medicine. However, existing herb recommendation systems are limited by data sparsity, insufficient correlation between pres...

Prognostic value of the Glucose-to-Albumin ratio in sepsis-related mortality: A retrospective ICU study.

AIMS: To investigate the prognostic value of the glucose-to-albumin ratio (GAR) in predicting 30-day and 90-day mortality in septic ICU patients.

Attention to early stages: predicting acute kidney injury in a post cardiosurgical ICU setting using an inclusive time-to-event model.

BACKGROUND: Acute kidney injury (AKI) is a critical complication in intensive care units (ICUs) that is known to have multifaceted impacts. However, a...

MIRAGE: Assessing Hallucination in Multimodal Reasoning Chains of MLLM

Multimodal hallucination in multimodal large language models (MLLMs) restricts the correctness of MLLMs. However, multimodal hallucinations are mult...

Intelligent Prediction Platform for Sepsis Risk Based on Real-Time Dynamic Temporal Features: Design Study.

BACKGROUND: The development of sepsis in the intensive care unit (ICU) is rapid, the golden rescue time is short, and the effective way to reduce mort...

MMSI-Bench: A Benchmark for Multi-Image Spatial Intelligence

Spatial intelligence is essential for multimodal large language models (MLLMs) operating in the complex physical world. Existing benchmarks, however...

ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations

Multi-modal large language models have demonstrated remarkable zero-shot abilities and powerful image-understanding capabilities. However, the exist...

Patient-Aware Feature Alignment for Robust Lung Sound Classification:Cohesion-Separation and Global Alignment Losses

Lung sound classification is vital for early diagnosis of respiratory diseases. However, biomedical signals often exhibit inter-patient variability ...

Spa-VLM: Stealthy Poisoning Attacks on RAG-based VLM

With the rapid development of the Vision-Language Model (VLM), significant progress has been made in Visual Question Answering (VQA) tasks. However,...

Development and Validation of SXI++ LNM Algorithm for Sepsis Prediction

Sepsis is a life-threatening condition affecting over 48.9 million people globally and causing 11 million deaths annually. Despite medical advanceme...

Zooming from Context to Cue: Hierarchical Preference Optimization for Multi-Image MLLMs

Multi-modal Large Language Models (MLLMs) excel at single-image tasks but struggle with multi-image understanding due to cross-modal misalignment, l...

BioHopR: A Benchmark for Multi-Hop, Multi-Answer Reasoning in Biomedical Domain

Biomedical reasoning often requires traversing interconnected relationships across entities such as drugs, diseases, and proteins. Despite the incre...

BioHopR: A Benchmark for Multi-Hop, Multi-Answer Reasoning in Biomedical Domain

Biomedical reasoning often requires traversing interconnected relationships across entities such as drugs, diseases, and proteins. Despite the incre...

A robust chronic obstructive pulmonary disease classification model using dragonfly optimized kernel extreme learning machine.

Chronic obstructive pulmonary disease (COPD) is considered to be one of the most commonly occurring respiratory disorders and is proliferating at an e...

STRATUS: A Multi-agent System for Autonomous Reliability Engineering of Modern Clouds

In cloud-scale systems, failures are the norm. A distributed computing cluster exhibits hundreds of machine failures and thousands of disk failures;...

Learning optimal treatment strategies for intraoperative hypotension using deep reinforcement learning

Traditional methods of surgical decision making heavily rely on human experience and prompt actions, which are variable. A data-driven system genera...

Simulating Ethics: Using LLM Debate Panels to Model Deliberation on Medical Dilemmas

This paper introduces ADEPT, a system using Large Language Model (LLM) personas to simulate multi-perspective ethical debates. ADEPT assembles panel...

Semi-supervised Clustering Through Representation Learning of Large-scale EHR Data

Electronic Health Records (EHR) offer rich real-world data for personalized medicine, providing insights into disease progression, treatment respons...

SELF-PERCEPT: Introspection Improves Large Language Models' Detection of Multi-Person Mental Manipulation in Conversations

Mental manipulation is a subtle yet pervasive form of abuse in interpersonal communication, making its detection critical for safeguarding potential...