Pulmonology

Development of a novel artificial intelligence algorithm to detect pulmonary nodules on chest radiography.

BACKGROUND: In this study, we aimed to develop a novel artificial intelligence (AI) algorithm to sup...

Developing a risk prediction tool for lung cancer in Kent and Medway, England: cohort study using linked data.

BACKGROUND: Lung cancer has the poorest survival due to late diagnosis and there is no universal scr...

Influenza Epidemic Trend Surveillance and Prediction Based on Search Engine Data: Deep Learning Model Study.

BACKGROUND: Influenza outbreaks pose a significant threat to global public health. Traditional surve...

Computer-aided diagnosis of chest X-ray for COVID-19 diagnosis in external validation study by radiologists with and without deep learning system.

To evaluate the diagnostic performance of our deep learning (DL) model of COVID-19 and investigate w...

Batch normalization followed by merging is powerful for phenotype prediction integrating multiple heterogeneous studies.

Heterogeneity in different genomic studies compromises the performance of machine learning models in...

Comparison of clinical efficacy of da Vinci robot-assisted lung cancer surgery with two-, three- and four-hole approaches.

Orifice reduction strategies for da Vinci robotic surgery have been a hot topic of research in recen...

A Deep Learning-Based Radiomic Classifier for Usual Interstitial Pneumonia.

BACKGROUND: Because chest CT scan has largely supplanted surgical lung biopsy for diagnosing most ca...

Continuous visualization and validation of pain in critically ill patients using artificial intelligence: a retrospective observational study.

Machine learning tools have demonstrated viability in visualizing pain accurately using vital sign d...

Localization and phenotyping of tuberculosis bacteria using a combination of deep learning and SVMs.

Successful treatment of pulmonary tuberculosis (TB) depends on early diagnosis and careful monitorin...

Development and validation of a CT-based deep learning algorithm to augment non-invasive diagnosis of idiopathic pulmonary fibrosis.

RATIONALE: Non-invasive diagnosis of idiopathic pulmonary fibrosis (IPF) involves identification of ...

Evaluation of the cytotoxic effect of titanium dioxide nanoparticles in human embryonic lung cells.

BACKGROUND/AIM: Titanium dioxide nanoparticles are widely used in a variety of products, including s...

Detection and severity quantification of pulmonary embolism with 3D CT data using an automated deep learning-based artificial solution.

PURPOSE: The purpose of this study was to propose a deep learning-based approach to detect pulmonary...

Volumetric tumor tracking from a single cone-beam X-ray projection image enabled by deep learning.

Radiotherapy serves as a pivotal treatment modality for malignant tumors. However, the accuracy of r...

Automatic Quantification of COVID-19 Pulmonary Edema by Self-supervised Contrastive Learning.

We proposed a self-supervised machine learning method to automatically rate the severity of pulmonar...

Development and Validation of a Deep Learning Radiomics Model to Predict High-Risk Pathologic Pulmonary Nodules Using Preoperative Computed Tomography.

RATIONALE AND OBJECTIVES: To accurately identify the high-risk pathological factors of pulmonary nod...

Deep learning-based solid component measuring enabled interpretable prediction of tumor invasiveness for lung adenocarcinoma.

BACKGROUND: The nature of the solid component of subsolid nodules (SSNs) can indicate tumor patholog...

Improving diagnosis accuracy with an intelligent image retrieval system for lung pathologies detection: a features extractor approach.

Detecting lung pathologies is critical for precise medical diagnosis. In the realm of diagnostic met...

CryoREAD: de novo structure modeling for nucleic acids in cryo-EM maps using deep learning.

DNA and RNA play fundamental roles in various cellular processes, where their three-dimensional stru...

Deep Learning for Detection of Pneumothorax and Pleural Effusion on Chest Radiographs: Validation Against Computed Tomography, Impact on Resident Reading Time, and Interreader Concordance.

PURPOSE: To study the performance of artificial intelligence (AI) for detecting pleural pathology on...

External validation, radiological evaluation, and development of deep learning automatic lung segmentation in contrast-enhanced chest CT.

OBJECTIVES: There is a need for CT pulmonary angiography (CTPA) lung segmentation models. Clinical t...

Robotic Lung Transplantation: A Paradigm Shift in Surgical Strategy.