Pulmonology

>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. Water quality indices have time series characteristics and nonlinearity, but the existing models only focus on the forward time series when long short-term memory (LSTM) is introduced and do not consider the parallel computation on the model. Owing to this, a new neural network called LSTM-multihead ...

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 influences their quality of life. Generic treatment plans could be improved with the aid of computational models that account for patient-specific features such as breathing pattern, lung pathology and morphology. Therefore, we aim to develop and validate an automated computational framework for pa...

Toward the eradication of medical diagnostic errors.

The medical community does not broadcast the problem, but there are many studies that have reinforced a serious issue with diagnostic errors. A recent...

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 morbidity and mortality worldwide. Despite all available d...

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 at risk (OARs) is crucial. In the current clinica...

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 potential agents against virus-induced diseases. Viral ent...

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. Peritoneal fibroblasts are characterized by increase in t...

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 received extensive attention from researchers. Due t...

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 system for detecting fibrosing interstitial lung ...

Pediatric Pulmonary Function Assessment Using Artificial Intelligence with Cough Sounds.

Explainable deep learning diagnostic system for prediction of lung disease from medical images.

Around the globe, respiratory lung diseases pose a severe threat to human survival. Based on a central goal to reduce contiguous transmission from inf...

Comparing Traditional Regression and Machine Learning Models in Predicting Acute Respiratory Distress Syndrome Mortality.

Explainable deep learning-based survival prediction for non-small cell lung cancer patients undergoing radical radiotherapy.

BACKGROUND AND PURPOSE: Survival is frequently assessed using Cox proportional hazards (CPH) regression; however, CPH may be too simplistic as it assu...

Point-of-care diagnosis of tissue fibrosis: a review of advances in vibrational spectroscopy with machine learning.

Histopathology is the gold standard for diagnosing fibrosis, but its routine use is constrained by the need for additional stains, time, personnel and...

Risk factors and clinical significance of subcutaneous emphysema after robot-assisted laparoscopic rectal surgery: a single-center experience.

Subcutaneous emphysema (SE) is a complication of laparoscopic surgery, potentially resulting in severe respiratory failure. No reports to date have fo...

MI-DenseCFNet: deep learning-based multimodal diagnosis models for Aureus and Aspergillus pneumonia.

OBJECTIVE: To build and merge a diagnostic model called multi-input DenseNet fused with clinical features (MI-DenseCFNet) for discriminating between S...

A deep learning-based algorithm improves radiology residents' diagnoses of acute pulmonary embolism on CT pulmonary angiograms.

PURPOSE: To compare radiology residents' diagnostic performances to detect pulmonary emboli (PEs) on CT pulmonary angiographies (CTPAs) with deep-lear...

Hyperpolarized Gas Imaging in Lung Diseases: Functional and Artificial Intelligence Perspective.

Pathophysiologic changes in lung diseases are often accompanied by changes in ventilation and gas exchange. Comprehensive evaluation of lung function ...