Pulmonology

Predicting early mortality and severe intraventricular hemorrhage in very-low birth weight preterm infants: a nationwide, multicenter study using machine learning.

Our aim was to develop a machine learning-based predictor for early mortality and severe intraventri...

Impact of rapid iodine contrast agent infusion on tracheal diameter and lung volume in CT pulmonary angiography measured with deep learning-based algorithm.

PURPOSE: To compare computed tomography (CT) pulmonary angiography and unenhanced CT to determine th...

Machine Learning Quantification of Pulmonary Regurgitation Fraction from Echocardiography.

Assessment of pulmonary regurgitation (PR) guides treatment for patients with congenital heart disea...

Accuracy of machine learning in preoperative identification of genetic mutation status in lung cancer: A systematic review and meta-analysis.

BACKGROUND AND PURPOSE: We performed this systematic review and meta-analysis to investigate the per...

Evaluating artificial intelligence responses to respiratory medicine questions.

Cross-site validation of lung cancer diagnosis by electronic nose with deep learning: a multicenter prospective study.

BACKGROUND: Although electronic nose (eNose) has been intensively investigated for diagnosing lung c...

Giving a Voice to Patients With Smell Disorders Associated With COVID-19: Cross-Sectional Longitudinal Analysis Using Natural Language Processing of Self-Reports.

BACKGROUND: Smell disorders are commonly reported with COVID-19 infection. The smell-related issues ...

Predicting drug-Protein interaction with deep learning framework for molecular graphs and sequences: Potential candidates against SAR-CoV-2.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the COVID-19 disease, which ...

Evaluation of image quality on low contrast media with deep learning image reconstruction algorithm in prospective ECG-triggering coronary CT angiography.

To assess the impact of low-dose contrast media (CM) injection protocol with deep learning image rec...

Impact of deep learning image reconstruction on volumetric accuracy and image quality of pulmonary nodules with different morphologies in low-dose CT.

BACKGROUND: This study systematically compares the impact of innovative deep learning image reconstr...

Graphene and metal-organic framework hybrids for high-performance sensors for lung cancer biomarker detection supported by machine learning augmentation.

Conventional diagnostic methods for lung cancer, based on breath analysis using gas chromatography a...

Weakly-Supervised Segmentation-Based Quantitative Characterization of Pulmonary Cavity Lesions in CT Scans.

OBJECTIVE: Pulmonary cavity lesion is one of the commonly seen lesions in lung caused by a variety o...

A reliable deep-learning-based method for alveolar bone quantification using a murine model of periodontitis and micro-computed tomography imaging.

OBJECTIVES: This study focuses on artificial intelligence (AI)-assisted analysis of alveolar bone fo...

A comprehensive study on machine learning models combining with oversampling for bronchopulmonary dysplasia-associated pulmonary hypertension in very preterm infants.

BACKGROUND: Bronchopulmonary dysplasia-associated pulmonary hypertension (BPD-PH) remains a devastat...

Interface design of SARS-CoV-2 symmetrical nsp7 dimer and machine learning-guided nsp7 sequence prediction reveals physicochemical properties and hotspots for nsp7 stability, adaptation, and therapeutic design.

The COVID-19 pandemic, driven by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), neces...

Development and external validation of a multimodal integrated feature neural network (MIFNN) for the diagnosis of malignancy in small pulmonary nodules (≤10 mm).

. Current lung cancer screening protocols primarily evaluate pulmonary nodules, yet often neglect th...

Artificial Intelligence in Laryngology, Broncho-Esophagology, and Sleep Surgery.

Technological advancements in laryngology, broncho-esophagology, and sleep surgery have enabled the ...

RSV Severe Infection Risk Stratification in a French 5-Year Birth Cohort Using Machine-learning.

BACKGROUND: Respiratory syncytial virus (RSV) poses a substantial threat to infants, often leading t...

Precise and automated lung cancer cell classification using deep neural network with multiscale features and model distillation.

Lung diseases globally impose a significant pathological burden and mortality rate, particularly the...

Air pollution and mortality for cancer of the respiratory system in Italy: an explainable artificial intelligence approach.

Respiratory system cancer, encompassing lung, trachea and bronchus cancer, constitute a substantial ...

An extensive review on lung cancer therapeutics using machine learning techniques: state-of-the-art and perspectives.

There are over 100 types of human cancer, accounting for millions of deaths every year. Lung cancer ...