Pulmonology

Latest AI and machine learning research in pulmonology for healthcare professionals.

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Evolving role of point-of-care ultrasound in prehospital emergency care: a narrative review.

Point-of-care ultrasound is an emerging technology in prehospital emergency care, covering a wide ra...

AI-driven wastewater management through comparative analysis of feature selection techniques and predictive models.

The integration of artificial intelligence (AI) in wastewater treatment management offers a promisin...

Chloride ion-capturing LaSrBO (B = Fe, Co) perovskite oxides achieving superior electrochemical desalination performance.

Perovskite oxides (ABO), with a designable crystal structure, excellent conductivity and inherent ox...

Establishing an AI-based diagnostic framework for pulmonary nodules in computed tomography.

BACKGROUND: Pulmonary nodules seen by computed tomography (CT) can be benign or malignant, and early...

Identification of right ventricular dysfunction with LogNNet based diagnostic model: A comparative study with supervised ML algorithms.

Right ventricular dysfunction (RVD) is strongly associated with increased mortality in patients with...

Progressive Learning-Guided Discovery of Single-Atom Metal Oxide Catalysts for Acidic Oxygen Evolution Reaction.

The oxygen evolution reaction (OER) is a key bottleneck in clean energy conversion due to sluggish k...

Seeing is Believing-On the Utility of CT in Phenotyping COPD.

Chronic obstructive pulmonary disease (COPD) is a heterogeneous condition with complicated structura...

Machine learning-based prediction of antimicrobial resistance and identification of AMR-related SNPs in Mycobacterium tuberculosis.

BACKGROUND: Mycobacterium tuberculosis (MTB) is a human-specific pathogen that primarily infects hum...

Neural network based AI model for lung health assessment.

Treating pulmonary diseases is pivotal in healthcare since they are the third leading cause of morta...

Self-Assembly MXene/PDA@Cotton Fabric Pressure Sensor Integrated with Deep Learning for Sign Language Recognition.

In recent years, smart textiles and flexible wearable products have garnered significant attention i...

Machine Learning-Assisted Multimodal Early Screening of Lung Cancer Based on a Multiplexed Laser-Induced Graphene Immunosensor.

Lung cancer remains the leading cause of cancer-related mortality worldwide, largely due to late-sta...

Machine Learning for Genomic Profiling and Drug Discovery in Personalised Lung Cancer Therapeutics.

Lung cancer is a prevalent and lethal malignancy characterised by the uncontrolled growth of abnorma...

Effect of data-driven motion correction for respiratory movement on lesion detectability in PET-CT: a phantom study.

PURPOSE: While data-driven motion correction (DDMC) techniques have proven to enhance the visibility...

Artificial Intelligence Performance in Pediatric Asthma.

OBJECTIVE: Asthma is the most common chronic disease of childhood, characterized by symptoms such as...

RadientFusion-XR: A Hybrid LBP-HOG Model for COVID-19 Detection Using Machine Learning.

The rapid and accurate detection of COVID-19 (coronavirus disease 2019) from normal and pneumonia ch...

FCRNet: Fast Fourier convolutional residual network for ventilator bearing fault diagnosis.

This study presents FCRNet, a Fast Fourier Convolution Residual Network, tailored for fault diagnosi...

Machine learning identifies lipid-associated genes and constructs diagnostic and prognostic models for idiopathic pulmonary fibrosis.

OBJECTIVE: Emerging evidence suggests a potential relationship between lipid metabolism and idiopath...

Application progress of machine learning in patient-ventilator asynchrony during mechanical ventilation: a systematic review.

INTRODUCTION: Patient-ventilator asynchrony (PVA) is a common and harmful complication during mechan...

Inflammatory, fibrotic and endothelial biomarker profiles in COVID-19 patients during and following hospitalization.

Survivors of severe COVID-19 often suffer from long-term respiratory issues, but the molecular drive...

Genome sequencing is critical for forecasting outcomes following congenital cardiac surgery.

While exome and whole genome sequencing have transformed medicine by elucidating the genetic underpi...

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