Pulmonology

Lung-DT: An AI-Powered Digital Twin Framework for Thoracic Health Monitoring and Diagnosis.

The integration of artificial intelligence (AI) with Digital Twins (DTs) has emerged as a promising ...

Machine learning predicted fast progression after initiation of immune checkpoint inhibitors in advanced non-small cell lung cancer.

Heterogeneous fusion of biometric and deep physiological features for accurate porcine cough recognition.

Accurate identification of porcine cough plays a vital role in comprehensive respiratory health moni...

Deep-Learning Reconstruction of High-Resolution CT Improves Interobserver Agreement for the Evaluation of Pulmonary Fibrosis.

This study aimed to investigate whether deep-learning reconstruction (DLR) improves interobserver a...

A three-gene random forest model for diagnosing idiopathic pulmonary fibrosis based on circadian rhythm-related genes in lung tissue.

BACKGROUND: The disorder of circadian rhythm could be a key factor mediating fibrotic lung disease T...

Improved image quality in CT pulmonary angiography using deep learning-based image reconstruction.

We investigated the effect of deep learning-based image reconstruction (DLIR) compared to iterative ...

Deep learning for real-time multi-class segmentation of artefacts in lung ultrasound.

Lung ultrasound (LUS) has emerged as a safe and cost-effective modality for assessing lung health, p...

Artificial Intelligence for the Detection of Pneumothorax on Chest Radiograph: Not yet the Panacea.

A bipolar intuitionistic fuzzy decision-making model for selection of effective diagnosis method of tuberculosis.

OBJECTIVES: Tuberculosis (TB) is a contagious illness caused by Mycobacterium tuberculosis. The init...

Diagnostic performance of deep learning models versus radiologists in COVID-19 pneumonia: A systematic review and meta-analysis.

PURPOSE: Although several studies have compared the performance of deep learning (DL) models and rad...

>Water quality prediction of artificial intelligence model: a case of Huaihe River Basin, China.

Accurate prediction of water quality contributes to the intelligent management of water resources. W...

Validated respiratory drug deposition predictions from 2D and 3D medical images with statistical shape models and convolutional neural networks.

For the one billion sufferers of respiratory disease, managing their disease with inhalers crucially...

Toward the eradication of medical diagnostic errors.

The medical community does not broadcast the problem, but there are many studies that have reinforce...

Demystification of artificial intelligence for respiratory clinicians managing patients with obstructive lung diseases.

INTRODUCTION: Asthma and chronic obstructive pulmonary disease (COPD) are leading causes of morbidit...

Use of artificial intelligence and radiomics for risk stratification in patients with pulmonary embolism: New tools for an old problem.

Clinical assessment of deep learning-based uncertainty maps in lung cancer segmentation.

. Prior to radiation therapy planning, accurate delineation of gross tumour volume (GTVs) and organs...

COPD: artificial intelligence detects and quantifies anomalies on chest CT enabling prediction of disease severity.

iDVEIP: A computer-aided approach for the prediction of viral entry inhibitory peptides.

With the notable surge in therapeutic peptide development, various peptides have emerged as potentia...

Unravelling the role of Sildenafil and SB204741 in suppressing fibrotic potential of peritoneal fibroblasts obtained from PD patients.

Peritoneal fibrosis (PF) results in technique failure in peritoneal dialysis (PD) patients. Periton...

Detection of fibrosing interstitial lung disease-suspected chest radiographs using a deep learning-based computer-aided detection system: a retrospective, observational study.

OBJECTIVES: To investigate the effectiveness of BMAX, a deep learning-based computer-aided detection...

Pneumonia detection based on RSNA dataset and anchor-free deep learning detector.

Pneumonia is a highly lethal disease, and research on its treatment and early screening tools has re...