Pulmonology

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.

Predicting the therapeutic efficacy of AIT for asthma using clinical characteristics, serum allergen detection metrics, and machine learning techniques.

Bronchial asthma is a prevalent non-communicable disease among children. The study collected clinica...

Deep Learning for Detecting Multi-Level Driver Fatigue Using Physiological Signals: A Comprehensive Approach.

A large share of traffic accidents is related to driver fatigue. In recent years, many studies have ...

The impact of deep learning reconstruction in low dose computed tomography on the evaluation of interstitial lung disease.

To evaluate the effect of the deep learning model reconstruction (DLM) method in terms of image qual...

DeepHistoNet: A robust deep-learning model for the classification of hepatocellular, lung, and colon carcinoma.

In recent days, non-communicable diseases (NCDs) require more attention since they require specializ...

Deep learning-based lung sound analysis for intelligent stethoscope.

Auscultation is crucial for the diagnosis of respiratory system diseases. However, traditional steth...

Point-wise spatial network for identifying carcinoma at the upper digestive and respiratory tract.

PROBLEM: Artificial intelligence has been widely investigated for diagnosis and treatment strategy d...

Push forward LC-MS-based therapeutic drug monitoring and pharmacometabolomics for anti-tuberculosis precision dosing and comprehensive clinical management.

The spread of tuberculosis (TB), especially multidrug-resistant TB and extensively drug-resistant TB...

Extracting lung contour deformation features with deep learning for internal target motion tracking: a preliminary study.

. To propose lung contour deformation features (LCDFs) as a surrogate to estimate the thoracic inter...

A comparison of 18 F-FDG PET-based radiomics and deep learning in predicting regional lymph node metastasis in patients with resectable lung adenocarcinoma: a cross-scanner and temporal validation study.

OBJECTIVE: The performance of 18 F-FDG PET-based radiomics and deep learning in detecting pathologic...

SelANet: decision-assisting selective sleep apnea detection based on confidence score.

BACKGROUND: One of the most common sleep disorders is sleep apnea syndrome. To diagnose sleep apnea ...

Autonomous medical needle steering in vivo.

The use of needles to access sites within organs is fundamental to many interventional medical proce...

Imaging of Solid Pulmonary Nodules.

Early detection with accurate classification of solid pulmonary nodules is critical in reducing lung...

PET/CT-based deep learning grading signature to optimize surgical decisions for clinical stage I invasive lung adenocarcinoma and biologic basis under its prediction: a multicenter study.

PURPOSE: No consensus on a grading system for invasive lung adenocarcinoma had been built over a lon...

Selecting cardiac magnetic resonance images suitable for annotation of pulmonary arteries using an active-learning based deep learning model.

An increasing and aging patient population poses a growing burden on healthcare professionals. Autom...

Deep Learning Neural Network-Guided Detection of Asbestos Bodies in Bronchoalveolar Lavage Samples.

INTRODUCTION: Asbestos is a global occupational health hazard, and exposure to it by inhalation pred...