Pulmonology

Deep learning for pneumothorax diagnosis: a systematic review and meta-analysis.

BACKGROUND: Deep learning (DL), a subset of artificial intelligence (AI), has been applied to pneumothorax diagnosis to aid physician diagnosis, but no meta-analysis has been performed.

A deep-learning model using enhanced chest CT images to predict PD-L1 expression in non-small-cell lung cancer patients.

AIM: To develop a deep-learning model using contrast-enhanced chest computed tomography (CT) images to predict programmed death-ligand 1 (PD-L1) expression in patients with non-small-cell lung cancer (NSCLC).

Leveraging human expert image annotations to improve pneumonia differentiation through human knowledge distillation.

In medical imaging, deep learning models can be a critical tool to shorten time-to-diagnosis and support specialized medical staff in clinical decisio...

Explainable COVID-19 Detection Based on Chest X-rays Using an End-to-End RegNet Architecture.

COVID-19,which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is one of the worst pandemics in recent history. The ide...

Deep-Learning Model of ResNet Combined with CBAM for Malignant-Benign Pulmonary Nodules Classification on Computed Tomography Images.

: Lung cancer remains a leading cause of cancer mortality worldwide. Accurately classifying benign pulmonary nodules and malignant ones is crucial for...

Redefining Lobe-Wise Ground-Glass Opacity in COVID-19 Through Deep Learning and its Correlation With Biochemical Parameters.

During COVID-19 pandemic qRT-PCR, CT scans and biochemical parameters were studied to understand the patients' physiological changes and disease progr...

Imaging of lung cancer.

Lung cancer is the leading cause of cancer-related mortality globally. Imaging is essential in the screening, diagnosis, staging, response assessment,...

Pneumonia detection with QCSA network on chest X-ray.

Worldwide, pneumonia is the leading cause of infant mortality. Experienced radiologists use chest X-rays to diagnose pneumonia and other respiratory d...

Remora Namib Beetle Optimization Enabled Deep Learning for Severity of COVID-19 Lung Infection Identification and Classification Using CT Images.

Coronavirus disease 2019 (COVID-19) has seen a crucial outburst for both females and males worldwide. Automatic lung infection detection from medical ...

Deep learning diagnostic and severity-stratification for interstitial lung diseases and chronic obstructive pulmonary disease in digital lung auscultations and ultrasonography: clinical protocol for an observational case-control study.

BACKGROUND: Interstitial lung diseases (ILD), such as idiopathic pulmonary fibrosis (IPF) and non-specific interstitial pneumonia (NSIP), and chronic ...

POLCOVID: a multicenter multiclass chest X-ray database (Poland, 2020-2021).

The outbreak of the SARS-CoV-2 pandemic has put healthcare systems worldwide to their limits, resulting in increased waiting time for diagnosis and re...

Detection of Multiple Respiration Patterns Based on 1D SNN from Continuous Human Breathing Signals and the Range Classification Method for Each Respiration Pattern.

Human respiratory information is being used as an important source of biometric information that can enable the analysis of health status in the healt...

Two- Versus 8-Zone Lung Ultrasound in Heart Failure: Analysis of a Large Data Set Using a Deep Learning Algorithm.

OBJECTIVE: Scanning protocols for lung ultrasound often include 8 or more lung zones, which may limit real-world clinical use. We sought to compare a ...

Predicting benefit from immune checkpoint inhibitors in patients with non-small-cell lung cancer by CT-based ensemble deep learning: a retrospective study.

BACKGROUND: Only around 20-30% of patients with non-small-cell lung cancer (NCSLC) have durable benefit from immune-checkpoint inhibitors. Although ti...

Deep Learning-Based IoT System for Remote Monitoring and Early Detection of Health Issues in Real-Time.

With an aging population and increased chronic diseases, remote health monitoring has become critical to improving patient care and reducing healthcar...

Machine learning-based drug design for identification of thymidylate kinase inhibitors as a potential anti-Mycobacterium tuberculosis.

The rise of antibiotic-resistant Mycobacterium tuberculosis (Mtb) has reduced the availability of medications for tuberculosis therapy, resulting in i...

A deep learning model enables accurate prediction and quantification of pulmonary edema from chest X-rays.

BACKGROUND: A quantitative assessment of pulmonary edema is important because the clinical severity can range from mild impairment to life threatening...

The artificial intelligence and machine learning in lung cancer immunotherapy.

Since the past decades, more lung cancer patients have been experiencing lasting benefits from immunotherapy. It is imperative to accurately and intel...

Diagnosis of Liver Fibrosis Using Artificial Intelligence: A Systematic Review.

The development of liver fibrosis as a consequence of continuous inflammation represents a turning point in the evolution of chronic liver diseases. ...

Artificial intelligence predicts lung cancer radiotherapy response: A meta-analysis.

BACKGROUND: Artificial intelligence (AI) technology has clustered patients based on clinical features into sub-clusters to stratify high-risk and low-...