Pulmonology

Predictive model for acute respiratory distress syndrome events in ICU patients in China using machine learning algorithms: a secondary analysis of a cohort study.

BACKGROUND: To develop a machine learning model for predicting acute respiratory distress syndrome (...

Clinical Study on Minimally Invasive Liquefaction and Drainage of Hypertensive Putaminal Hemorrhage through Frontal Approach.

 Hypertensive intracerebral hemorrhage is one of the most common cerebrovascular diseases with high...

Robotic anatomic pulmonary segmentectomy: technical approach and outcomes.

OBJECTIVE: to report our initial experience with pulmonary robotic segmentectomy, describing the sur...

Comparison of CT and MRI images for the prediction of soft-tissue sarcoma grading and lung metastasis via a convolutional neural networks model.

AIM: To realise the automated prediction of soft-tissue sarcoma (STS) grading and lung metastasis ba...

The role of AI in diagnosing lung diseases.

Deep learning-enabled system for rapid pneumothorax screening on chest CT.

PURPOSE: Prompt diagnosis and quantitation of pneumothorax impact decisions pertaining to patient ma...

Prediction of complication related death after radical cystectomy for bladder cancer with machine learning methodology.

To create a pre-operatively usable tool to identify patients at high risk of early death (within 90...

Commentary: Robotic anatomic lung resection: Raising the bar of our expectations in treating lung cancer.

Commentary: Robotic anatomic pulmonary resection: Cinderella has left the house.

Deep learning to convert unstructured CT pulmonary angiography reports into structured reports.

BACKGROUND: Structured reports have been shown to improve communication between radiologists and pro...

Single patient convolutional neural networks for real-time MR reconstruction: a proof of concept application in lung tumor segmentation for adaptive radiotherapy.

Investigate 3D (spatial and temporal) convolutional neural networks (CNNs) for real-time on-the-fly ...

An Individualized Prediction Model for Long-term Lung Function Trajectory and Risk of COPD in the General Population.

BACKGROUND: Prediction of future lung function will enable the identification of individuals at high...

Detection of Lung Cancer Lymph Node Metastases from Whole-Slide Histopathologic Images Using a Two-Step Deep Learning Approach.

The application of deep learning for the detection of lymph node metastases on histologic slides has...

Levels of Soluble Urokinase Plasminogen Activator Receptor in Pediatric Lower Respiratory Tract Infections.

Lower respiratory tract infections (LTRIs) are the most common cause of pediatric emergency departm...

Artificial neural network analysis of the oxygen saturation signal enables accurate diagnostics of sleep apnea.

The severity of obstructive sleep apnea (OSA) is classified using apnea-hypopnea index (AHI). Accura...

Identifying pulmonary nodules or masses on chest radiography using deep learning: external validation and strategies to improve clinical practice.

AIM: To test the diagnostic performance of a deep learning-based system for the detection of clinica...

2D ultrasound imaging based intra-fraction respiratory motion tracking for abdominal radiation therapy using machine learning.

We have previously developed a robotic ultrasound imaging system for motion monitoring in abdominal ...

Toward predicting the evolution of lung tumors during radiotherapy observed on a longitudinal MR imaging study via a deep learning algorithm.

PURPOSE: To predict the spatial and temporal trajectories of lung tumor during radiotherapy monitore...

A large cohort study identifying a novel prognosis prediction model for lung adenocarcinoma through machine learning strategies.

BACKGROUND: Predicting lung adenocarcinoma (LUAD) risk is crucial in determining further treatment s...

Long-term follow-up of persistent pulmonary pure ground-glass nodules with deep learning-assisted nodule segmentation.

OBJECTIVE: To investigate the natural history of persistent pulmonary pure ground-glass nodules (pGG...

Predicting lung nodule malignancies by combining deep convolutional neural network and handcrafted features.

To predict lung nodule malignancy with a high sensitivity and specificity for low dose CT (LDCT) lun...