Pulmonology

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

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Deep learning-based approach for acquisition time reduction in ventilation SPECT in patients after lung transplantation.

We aimed to evaluate the image quality and diagnostic performance of chronic lung allograft dysfunct...

Lung nodule classification using radiomics model trained on degraded SDCT images.

BACKGROUND AND OBJECTIVE: Low-dose computed tomography (LDCT) screening has shown promise in reducin...

Noninvasive biometric monitoring technologies for patients with heart failure.

Heart failure remains one of the leading causes of mortality and hospitalizations in the US that not...

Multimodal ultrasound deep learning to detect fibrosis in early chronic kidney disease.

We developed a multimodal ultrasound (US) deep learning (DL) fusion model to automatically classify ...

Auto encoder-based defense mechanism against popular adversarial attacks in deep learning.

Convolutional Neural Network (CNN)-based models are prone to adversarial attacks, which present a si...

Machine learning models of cerebral oxygenation (rcSO) for brain injury detection in neonates with hypoxic-ischaemic encephalopathy.

The present study was designed to test the potential utility of regional cerebral oxygen saturation ...

Mastery Learning Guided by Artificial Intelligence Is Superior to Directed Self-Regulated Learning in Flexible Bronchoscopy Training: An RCT.

INTRODUCTION: Simulation-based training has proven effective for learning flexible bronchoscopy. How...

Amaurosis after Inferior Alveolar Nerve Block Injection in a Seven-Year-Old Girl: A Case Report and Review of the Literature.

A seven-year-old girl was referred for the treatment of her primary teeth. An inferior alveolar nerv...

Rapid On-Site Histology of Lung and Pleural Biopsies Using Higher Harmonic Generation Microscopy and Artificial Intelligence Analysis.

Lung cancer is one of the most prevalent and lethal cancers. To improve health outcomes while reduci...

Machine learning-derived peripheral blood transcriptomic biomarkers for early lung cancer diagnosis: Unveiling tumor-immune interaction mechanisms.

Lung cancer continues to be the leading cause of cancer-related mortality worldwide. Early detection...

Machine learning algorithms to predict treatment success for patients with pulmonary tuberculosis.

Despite advancements in detection and treatment, tuberculosis (TB), an infectious illness caused by ...

Predicting photosynthetic bacteria-derived protein synthesis from wastewater using machine learning and causal inference.

Causal inference-assisted machine learning was used to predict photosynthetic bacterial (PSB) protei...

Machine Learning Early Detection of SARS-CoV-2 High-Risk Variants.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has evolved many high-risk variants...

Assessing prospective molecular biomarkers and functional pathways in severe asthma based on a machine learning method and bioinformatics analyses.

BACKGROUND: Severe asthma, which differs significantly from typical asthma, involves specific molecu...

Integrative multi-omic and machine learning approach for prognostic stratification and therapeutic targeting in lung squamous cell carcinoma.

The proliferation, metastasis, and drug resistance of cancer cells pose significant challenges to th...

Combining bioinformatics and machine learning to identify diagnostic biomarkers of TB associated with immune cell infiltration.

OBJECTIVE: The asymptomatic nature of tuberculosis (TB) during its latent phase, combined with limit...

Application of a Deep Learning-Based Contrast-Boosting Algorithm to Low-Dose Computed Tomography Pulmonary Angiography With Reduced Iodine Load.

OBJECTIVE: The aim of this study was to assess the effectiveness of a deep learning-based image cont...

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