Critical Care

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, and hospitals. Most traditional multi-target multi-camera (MTMC) detection and tracking methods rely on 2D object detection, single-view multi-object tracking (MOT), and cross-view re-identification (ReID) techniques, without properly handling import...

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), which increases mortality risks. Investigating the prognostic implications of ARDS-related genes in LUAD is crucial for improving clinical outcomes. Data from TCGA, GEO and GTEx were used to identify 276 ARDS-related genes in LUAD via differential...

A Respiratory Signal Monitoring Method Based on Dual-Pathway Deep Learning Networks in Image-Guided Robotic-Assisted Intervention System.

BACKGROUND: Percutaneous puncture procedures, guided by image-guided robotic-assisted intervention (IGRI) systems, are susceptible to disruptions in p...

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...

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence

Cyber-attacks pose a security threat to military command and control networks, Intelligence, Surveillance, and Reconnaissance (ISR) systems, and civ...

MIN: Multi-channel Interaction Network for Drug-Target Interaction with Protein Distillation

Traditional drug discovery processes are both time-consuming and require extensive professional expertise. With the accumulation of drug-target inte...

Multi-view multi-level contrastive graph convolutional network for cancer subtyping on multi-omics data.

Cancer is a highly diverse group of diseases, and each type of cancer can be further divided into various subtypes according to specific characteristi...

Identity Preserving 3D Head Stylization with Multiview Score Distillation

3D head stylization transforms realistic facial features into artistic representations, enhancing user engagement across gaming and virtual reality ...

Pruning the Path to Optimal Care: Identifying Systematically Suboptimal Medical Decision-Making with Inverse Reinforcement Learning

In aims to uncover insights into medical decision-making embedded within observational data from clinical settings, we present a novel application o...

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)...

Residual Multi-Task Learner for Applied Ranking

Modern e-commerce platforms rely heavily on modeling diverse user feedback to provide personalized services. Consequently, multi-task learning has b...

On-Site Precise Screening of SARS-CoV-2 Systems Using a Channel-Wise Attention-Based PLS-1D-CNN Model with Limited Infrared Signatures

During the early stages of respiratory virus outbreaks, such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the efficient utilize ...

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...

Comparative Analysis of Multi-Omics Integration Using Advanced Graph Neural Networks for Cancer Classification

Multi-omics data is increasingly being utilized to advance computational methods for cancer classification. However, multi-omics data integration po...

M$^{2}$M: Learning controllable Multi of experts and multi-scale operators are the Partial Differential Equations need

Learning the evolutionary dynamics of Partial Differential Equations (PDEs) is critical in understanding dynamic systems, yet current methods insuff...

[Bowel Sounds Detection Method Based on ResNet-BiLSTM and Attention Mechanism].

Bowel sounds can reflect the movement and health status of the gastrointestinal tract. However, the traditional manual auscultation method has subject...

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...

GATher: Graph Attention Based Predictions of Gene-Disease Links

Target selection is crucial in pharmaceutical drug discovery, directly influencing clinical trial success. Despite its importance, drug development ...

PRAGA: Prototype-aware Graph Adaptive Aggregation for Spatial Multi-modal Omics Analysis

Spatial multi-modal omics technology, highlighted by Nature Methods as an advanced biological technique in 2023, plays a critical role in resolving ...