Pulmonology

Prospective evaluation of deep learning image reconstruction for Lung-RADS and automatic nodule volumetry on ultralow-dose chest CT.

PURPOSE: To prospectively evaluate whether Lung-RADS classification and volumetric nodule assessment...

Robot-assisted thoracic surgery for benign tumors at the cervicothoracic junction: a propensity-matched study.

This study aimed to assess the feasibility and safety of robot-assisted thoracic surgery (RATS) for ...

Elevated Plasma CXCL8 Concentrations in Significant Fibrosis but Not in Subclinical Rejection After Adult Liver Transplantation.

BACKGROUND: The noninvasive detection of subclinical graft injury including subclinical T cell-media...

The importance of data in Pulmonary Arterial Hypertension: from international registries to Machine Learning.

Real-world registries have been critical to building the scientific knowledge of rare diseases, incl...

Fully automated deep learning model for detecting proximity of mandibular third molar root to inferior alveolar canal using panoramic radiographs.

OBJECTIVE: This study endeavored to develop a novel, fully automated deep-learning model to determin...

Machine learning assisted methods for the identification of low toxicity inhibitors of Enoyl-Acyl Carrier Protein Reductase (InhA).

Tuberculosis (TB) is one of the life-threatening infectious diseases with prehistoric origins and oc...

Intelligently Quantifying the Entire Irregular Dental Structure.

Quantitative analysis of irregular anatomical structures is crucial in oral medicine, but clinicians...

Application of artificial intelligence in diagnosis of pulmonary tuberculosis.

Artificial intelligence-enabled optimization of Fe/Zn@biochar photocatalyst for 2,6-dichlorophenol removal from petrochemical wastewater: A techno-economic perspective.

While numerous studies have addressed the photocatalytic degradation of 2,6-dichlorophenol (2,6-DCP)...

A deep learning-based framework (Co-ReTr) for auto-segmentation of non-small cell-lung cancer in computed tomography images.

PURPOSE: Deep learning-based auto-segmentation algorithms can improve clinical workflow by defining ...

COPD stage detection: leveraging the auto-metric graph neural network with inspiratory and expiratory chest CT images.

Chronic obstructive pulmonary disease (COPD) is a common lung disease that can lead to restricted ai...

Automated Real-Time Detection of Lung Sliding Using Artificial Intelligence: A Prospective Diagnostic Accuracy Study.

BACKGROUND: Rapid evaluation for pneumothorax is a common clinical priority. Although lung ultrasoun...

Deciphering the fibrotic process: mechanism of chronic radiation skin injury fibrosis.

This review explores the mechanisms of chronic radiation-induced skin injury fibrosis, focusing on t...

Machine learning models to evaluate mortality in pediatric patients with pneumonia in the intensive care unit.

OBJECTIVES: This study aimed to predict mortality in children with pneumonia who were admitted to th...

Enhancing heart failure treatment decisions: interpretable machine learning models for advanced therapy eligibility prediction using EHR data.

Timely and accurate referral of end-stage heart failure patients for advanced therapies, including h...

Potential of radiomics analysis and machine learning for predicting brain metastasis in newly diagnosed lung cancer patients.

AIM: To explore the potential of utilising radiomics analysis and machine-learning models that incor...

Accurate Liver Fibrosis Detection Through Hybrid MRMR-BiLSTM-CNN Architecture with Histogram Equalization and Optimization.

The early detection and accurate diagnosis of liver fibrosis, a progressive and potentially serious ...

Meta-lasso: new insight on infection prediction after minimally invasive surgery.

Surgical site infection (SSI) after minimally invasive lung cancer surgery constitutes an important ...

External validation of the RSNA 2020 pulmonary embolism detection challenge winning deep learning algorithm.

PURPOSE: To evaluate the diagnostic performance and generalizability of the winning DL algorithm of ...

METnet: A novel deep learning model predicting MET dysregulation in non-small-cell lung cancer on computed tomography images.

BACKGROUND: Mesenchymal epithelial transformation (MET) is a key molecular target for diagnosis and ...

Strong Diagnostic Performance of Single Energy 256-row Multidetector Computed Tomography with Deep Learning Image Reconstruction in the Assessment of Myocardial Fibrosis.

Objective Although magnetic resonance imaging (MRI) is the gold standard for evaluating abnormal myo...