Pulmonology

Network-Reconfigured Thermoelectric Flexible Sensor for Ultrafast Steady-State Temperature Perception.

Ultrafast and stable steady-state temperature perception is critically important for emerging applications such as electronic skin and intelligent human-machine interfaces, yet it remains a big challenge for flexible temperature sensors due to the difficulty in rapidly establishing and maintaining stable thermal gradients. Here, we propose a conductive/thermoelectric network reconfiguration strate...

Hierarchical Amplification-Interlinked CRISPR-Cas14a Luminescent Biosensor Coupled with Portable Photonic Crystal Biochip-Boosted Time-Delayed Signaling for the Diagnosis of Pediatric Mycoplasma pneumoniae Pneumonia.

Mycoplasma pneumoniae pneumonia (MPP) is a respiratory infection that readily propagates within pediatric populations, and thus, the development of a robust assay approach for its timely diagnosis is of clinical importance. In this contribution, we build a hierarchical amplification-interlinked CRISPR-Cas14a luminescent biosensor coupled with portable photonic crystal biochip-boosted time-delayed ...

A Spatiotemporal Transformer Framework on 4D-CT for Early Prediction of Progressive Pulmonary Fibrosis.

Progressive pulmonary fibrosis (PPF) remains difficult to predict because static imaging may not fully capture regional respiratory motion, ventilatio...

AI-Powered Resting 12-Lead Electrocardiogram Algorithm for Predicting Low Peak Oxygen Consumption: Development and Validation Study.

BACKGROUND: Low peak oxygen consumption (V̇O2) is associated with higher cardiovascular and all-cause mortality, while improvements in peak V̇O2 reduc...

Causal counterfactual simulation for treatment decisions in multimodal lung disease data.

While deep learning has advanced the automated diagnosis of pulmonary diseases from chest X-rays, transitioning these models to treatment optimisation...

A Novel Model to Predict Progression to Death After Withdrawal of Care in Potential Donation-After-Circulatory-Death Heart Donors.

BACKGROUND: Predicting successful heart donation after circulatory death (DCD) remains a challenge. We developed a model to predict progression to cir...

AI-Enhanced Point-of-Care Diagnostics for Infectious Diseases in Resource-Limited Settings: A Scoping Review.

OBJECTIVES: To systematically map the extent and nature of research on AI-enhanced point-of-care (POC) and rapid diagnostic technologies for infectiou...

Benchmarking large language models for cell-free RNA diagnostic biomarker discovery.

Large language models can synthesize biomedical knowledge, parse vast amounts of data, and generate code, positioning them as promising tools for biom...

Feature selection methodology based on explainable AI: application in predicting extubation success in the intensive care unit.

High-dimensional medical data hinder predictive modeling because of noise and the curse of dimensionality, making robust feature selection (FS) essent...

TriNet-MoE: One New Neural Network Framework Based on Mixture of Experts for CXR-Based COVID-19 Detection.

As a low-dose portable imaging technology, chest X-ray (CXR) is widely used for the screening of lung diseases, including COVID-19. However, existing ...

Transcriptomic analysis identifies novel ferroptosis-related biomarkers and therapeutic targets in pulmonary arterial hypertension.

BACKGROUND: Ferroptosis plays a significant role in pulmonary arterial hypertension (PAH), although its underlying mechanisms and key pathogenic genes...

Targeting emerging respiratory pathogens with Clamp Peptides: broad-spectrum inhibition of viral entry in 3D human lung models.

Rapid urbanization, migration and climate change are accelerating the appearance and diversification of respiratory viruses, overwhelming the pace at ...

Machine learning-based prediction of early invasive mechanical ventilation in ICU patients with pneumonia: Development and external validation.

BACKGROUND: Pneumonia is a common critical illness in the intensive care unit (ICU), and a subset of patients rapidly progresses to respiratory failur...

Extracranial vascular association of moyamoya disease: a systematic review and machine learning analysis.

BACKGROUND: Intracranial steno-occlusive lesions are characteristic of moyamoya disease (MMD), but increasing reports of extracranial vascular involve...

Predictive Model for Bone Availability in Patients With Unilateral Cleft Lip and Palate: A Machine Learning Approach.

ObjectiveTo develop a predictive model for estimating cortical bone thickness at any maxillary location in patients with unilateral cleft lip and pala...

Comparative evaluation of generative AI models for chest radiograph report generation in the emergency department.

OBJECTIVES: To benchmark medical image-specific vision-language models (VLMs) against real-world radiologist-written reports, focusing on diagnostic q...

Development and validation of a machine learning-based model for predicting delirium risk in postoperative brain tumor patients in the Intensive Care Unit.

OBJECTIVE: This study aimed to clarify the incidence and influencing factors of delirium in ICU patients after brain tumor surgery, construct and vali...

Robust Semi-Supervised CT Radiomics for Lung Cancer Prognosis: Cost-Effective Learning with Limited Labels and SHAP Interpretation.

OBJECTIVE: Computed tomography (CT) imaging is essential for lung cancer (LCa) management, while offering detailed visualization and valuable informat...

From DNA to Drug Discovery AI Models for Cardiovascular Precision Medicine.

Cardiovascular diseases remain the world's leading cause of death-yet the molecular mechanisms linking genetic variation to clinical outcomes are stil...

Association between the PaO2/FiO2-to-PaCO2 ratio and mortality in patients with sepsis: a retrospective study with dual-cohort validation.

BACKGROUND: Sepsis patients face a high mortality risk. Available prognostic biomarkers have certain limitations. This study explored the prognostic u...