Pulmonology

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

6,504 articles
Stay Ahead - Weekly Pulmonology research updates
Subscribe
Browse Categories
Showing 1198-1218 of 6,504 articles
An anthropomorphic diagnosis system of pulmonary nodules using weak annotation-based deep learning.

The accurate categorization of lung nodules in CT scans is an essential aspect in the prompt detecti...

Evaluating Explainable Artificial Intelligence (XAI) techniques in chest radiology imaging through a human-centered Lens.

The field of radiology imaging has experienced a remarkable increase in using of deep learning (DL) ...

DeepCOVIDNet-CXR: deep learning strategies for identifying COVID-19 on enhanced chest X-rays.

OBJECTIVES: COVID-19 is one of the recent major epidemics, which accelerates its mortality and preva...

Tracing the path from preschool wheezing to asthma.

This short review illustrates, using two recent studies, the potential and challenges of using machi...

Is artificial intelligence prepared for the 24-h shifts in the ICU?

Integrating machine learning (ML) into intensive care units (ICUs) can significantly enhance patient...

Preoperative markers for identifying CT ≤2 cm solid nodules of lung adenocarcinoma based on image deep learning.

BACKGROUND: The solid pattern is a highly malignant subtype of lung adenocarcinoma. In the current e...

Personalized prediction of immunotherapy response in lung cancer patients using advanced radiomics and deep learning.

BACKGROUND: Lung cancer (LC) is a leading cause of cancer-related mortality, and immunotherapy (IO) ...

Using random forest and biomarkers for differentiating COVID-19 and Mycoplasma pneumoniae infections.

The COVID-19 pandemic has underscored the critical need for precise diagnostic methods to distinguis...

A vision transformer-based deep transfer learning nomogram for predicting lymph node metastasis in lung adenocarcinoma.

BACKGROUND: Lymph node metastasis (LNM) plays a crucial role in the management of lung cancer; howev...

Using 3D point cloud and graph-based neural networks to improve the estimation of pulmonary function tests from chest CT.

Pulmonary function tests (PFTs) are important clinical metrics to measure the severity of interstiti...

Development and validation of machine learning models for diagnosis and prognosis of lung adenocarcinoma, and immune infiltration analysis.

The aim of our study was to develop robust diagnostic and prognostic models for lung adenocarcinoma ...

Length-scale study in deep learning prediction for non-small cell lung cancer brain metastasis.

Deep learning-assisted digital pathology has demonstrated the potential to profoundly impact clinica...

Deep-learning model accurately classifies multi-label lung ultrasound findings, enhancing diagnostic accuracy and inter-reader agreement.

Despite the increasing use of lung ultrasound (LUS) in the evaluation of respiratory disease, operat...

Browse Categories