Pulmonology

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

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Patient-ventilator asynchrony classification in mechanically ventilated patients: Model-based or machine learning method?

BACKGROUND AND OBJECTIVE: Patient-ventilator asynchrony (PVA) is associated with poor clinical outco...

Machine Learning Approach in Dosage Individualization of Isoniazid for Tuberculosis.

INTRODUCTION: Isoniazid is a first-line antituberculosis agent with high variability, which would pr...

Deep learning in pulmonary nodule detection and segmentation: a systematic review.

OBJECTIVES: The accurate detection and precise segmentation of lung nodules on computed tomography a...

Habitat radiomics and deep learning fusion nomogram to predict EGFR mutation status in stage I non-small cell lung cancer: a multicenter study.

Develop a radiomics nomogram that integrates deep learning, radiomics, and clinical variables to pre...

Artificial neural networks trained on simulated multispectral data for real-time imaging of skin microcirculatory blood oxygen saturation.

SIGNIFICANCE: Imaging blood oxygen saturation ( ) in the skin can be of clinical value when studyin...

Applications of artificial intelligence in computed tomography imaging for phenotyping pulmonary hypertension.

PURPOSE OF REVIEW: Pulmonary hypertension is a heterogeneous condition with significant morbidity an...

Artificial intelligence-based graded training of pulmonary nodules for junior radiology residents and medical imaging students.

BACKGROUND: To evaluate the efficiency of artificial intelligence (AI)-assisted diagnosis system in ...

Factors of acute respiratory infection among under-five children across sub-Saharan African countries using machine learning approaches.

Symptoms of Acute Respiratory infections (ARIs) among under-five children are a global health challe...

Exploring explainable AI features in the vocal biomarkers of lung disease.

This review delves into the burgeoning field of explainable artificial intelligence (XAI) in the det...

A deep learning-based model to estimate pulmonary function from chest x-rays: multi-institutional model development and validation study in Japan.

BACKGROUND: Chest x-ray is a basic, cost-effective, and widely available imaging method that is used...

Cross-attention enables deep learning on limited omics-imaging-clinical data of 130 lung cancer patients.

Deep-learning tools that extract prognostic factors derived from multi-omics data have recently cont...

Optimization of vision transformer-based detection of lung diseases from chest X-ray images.

BACKGROUND: Recent advances in Vision Transformer (ViT)-based deep learning have significantly impro...

Combining Federated Machine Learning and Qualitative Methods to Investigate Novel Pediatric Asthma Subtypes: Protocol for a Mixed Methods Study.

BACKGROUND: Pediatric asthma is a heterogeneous disease; however, current characterizations of its s...

COVID-19 and Pneumonia detection and web deployment from CT scan and X-ray images using deep learning.

During the COVID-19 pandemic, pneumonia was the leading cause of respiratory failure and death. In a...

Automatic semantic segmentation of EHG recordings by deep learning: An approach to a screening tool for use in clinical practice.

BACKGROUND AND OBJECTIVE: Preterm delivery is an important factor in the disease burden of the newbo...

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