Pulmonology

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

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Feature Separation in Diffuse Lung Disease Image Classification by Using Evolutionary Algorithm-Based NAS.

In the field of diagnosing lung diseases, the application of neural networks (NNs) in image classifi...

Machine learning approach for dosage individualization of azithromycin in children with community-acquired pneumonia.

AIMS: The uncertainty about the efficacy and safety of currently used azithromycin dosing regimens i...

An extension to the OVH concept for knowledge-based dose volume histogram prediction in lung tumor volumetric-modulated arc therapy.

PURPOSE: Volumetric-modulated arc therapy (VMAT) treatment planning allows a compromise between a su...

A Novel Theranostic Strategy for Malignant Pulmonary Nodules by Targeted CECAM6 with Zr/I-Labeled Tinurilimab.

Lung adenocarcinoma (LUAD) constitutes a major cause of cancer-related fatalities worldwide. Early i...

Artificial Intelligence for the Detection of Patient-Ventilator Asynchrony.

Patient-ventilator asynchrony (PVA) is a challenge to invasive mechanical ventilation characterized ...

Integrating a host transcriptomic biomarker with a large language model for diagnosis of lower respiratory tract infection.

BACKGROUND: Lower respiratory tract infections (LRTIs) are a leading cause of mortality worldwide an...

Large Language Models in Summarizing Radiology Report Impressions for Lung Cancer in Chinese: Evaluation Study.

BACKGROUND: Large language models (LLMs), such as ChatGPT, have demonstrated impressive capabilities...

Analysis of Multiple Programmed Cell Death Patterns and Functional Validations of Apoptosis-Associated Genes in Lung Adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is marked by its considerable aggressiveness and pronounced h...

Performance of Computer-Aided Detection Software in Tuberculosis Case Finding in Township Health Centers in China.

BACKGROUND: Computer-aided detection (CAD) software has been introduced to automatically interpret d...

Therapeutic potential of allosteric HECT E3 ligase inhibition.

Targeting ubiquitin E3 ligases is therapeutically attractive; however, the absence of an active-site...

Enhanced prediction of ventilator-associated pneumonia in patients with traumatic brain injury using advanced machine learning techniques.

Ventilator-associated pneumonia significantly increases morbidity, mortality, and healthcare costs a...

Addressing model discrepancy in a clinical model of the oxygen dissociation curve.

Many mathematical models suffer from model discrepancy, posing a significant challenge to their use ...

Advanced imaging techniques and artificial intelligence in pleural diseases: a narrative review.

BACKGROUND: Pleural diseases represent a significant healthcare burden, affecting over 350 000 patie...

Metabolomic machine learning-based model predicts efficacy of chemoimmunotherapy for advanced lung squamous cell carcinoma.

BACKGROUND: Unlike lung adenocarcinoma, patients with advanced squamous carcinoma exhibit a low prop...

Development and validation of machine learning models for early diagnosis and prognosis of lung adenocarcinoma using miRNA expression profiles.

ObjectiveStudy aims to develop diagnostic and prognostic models for lung adenocarcinoma (LUAD) using...

Improved unsupervised 3D lung lesion detection and localization by fusing global and local features: Validation in 3D low-dose computed tomography.

Unsupervised anomaly detection (UAD) is crucial in low-dose computed tomography (LDCT). Recent AI te...

Right ventricular dysfunction following tetralogy of Fallot correction: anatomical determinants and therapeutic strategies.

Right ventricular dysfunction following surgical correction of tetralogy of Fallot (TOF) remains a m...

A CNN-transformer fusion network for predicting high-grade patterns in stage IA invasive lung adenocarcinoma.

BACKGROUND: Invasive lung adenocarcinoma (LUAD) with the high-grade patterns (HGPs) has the potentia...

Predictive models of epidermal growth factor receptor mutation in lung adenocarcinoma using PET/CT-based radiomics features.

BACKGROUND: Lung adenocarcinoma (LAC) comprises a substantial subset of non-small cell lung cancer (...

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