Pulmonology

Pediatric Pulmonary Function Assessment Using Artificial Intelligence with Cough Sounds.

Explainable deep learning diagnostic system for prediction of lung disease from medical images.

Around the globe, respiratory lung diseases pose a severe threat to human survival. Based on a centr...

Comparing Traditional Regression and Machine Learning Models in Predicting Acute Respiratory Distress Syndrome Mortality.

Point-of-care diagnosis of tissue fibrosis: a review of advances in vibrational spectroscopy with machine learning.

Histopathology is the gold standard for diagnosing fibrosis, but its routine use is constrained by t...

Explainable deep learning-based survival prediction for non-small cell lung cancer patients undergoing radical radiotherapy.

BACKGROUND AND PURPOSE: Survival is frequently assessed using Cox proportional hazards (CPH) regress...

Risk factors and clinical significance of subcutaneous emphysema after robot-assisted laparoscopic rectal surgery: a single-center experience.

Subcutaneous emphysema (SE) is a complication of laparoscopic surgery, potentially resulting in seve...

MI-DenseCFNet: deep learning-based multimodal diagnosis models for Aureus and Aspergillus pneumonia.

OBJECTIVE: To build and merge a diagnostic model called multi-input DenseNet fused with clinical fea...

A deep learning-based algorithm improves radiology residents' diagnoses of acute pulmonary embolism on CT pulmonary angiograms.

PURPOSE: To compare radiology residents' diagnostic performances to detect pulmonary emboli (PEs) on...

Hyperpolarized Gas Imaging in Lung Diseases: Functional and Artificial Intelligence Perspective.

Pathophysiologic changes in lung diseases are often accompanied by changes in ventilation and gas ex...

Long-term results of ablation index guided atrial fibrillation ablation: insights after 5+ years of follow-up from the MPH AF Ablation Registry.

BACKGROUND: Catheter ablation (CA) for symptomatic atrial fibrillation (AF) offers the best outcomes...

Could the underlying biological basis of prognostic radiomics and deep learning signatures be explored in patients with lung cancer? A systematic review.

OBJECTIVES: To summarize the underlying biological correlation of prognostic radiomics and deep lear...

Perioperative Fluid and Vasopressor Therapy in 2050: From Experimental Medicine to Personalization Through Automation.

Intravenous (IV) fluids and vasopressor agents are key components of hemodynamic management. Since t...

Computer-aided diagnosis of distal metastasis in non-small cell lung cancer by low-dose CT based radiomics and deep learning signatures.

BACKGROUND: This study aimed to develop and validate radiomics and deep learning (DL) signatures for...

Predicting occult lymph node metastasis in solid-predominantly invasive lung adenocarcinoma across multiple centers using radiomics-deep learning fusion model.

BACKGROUND: In solid-predominantly invasive lung adenocarcinoma (SPILAC), occult lymph node metastas...

Corrigendum: An attention-based deep learning network for lung nodule malignancy discrimination.

[This corrects the article DOI: 10.3389/fnins.2022.1106937.].

Early prediction of pediatric asthma in the Canadian Healthy Infant Longitudinal Development (CHILD) birth cohort using machine learning.

BACKGROUND: Early identification of children at risk of asthma can have significant clinical implica...

Higher rating of perceived exertion and lower perceived recovery following a graded exercise test during menses compared to non-bleeding days in untrained females.

The underrepresentation of the female population in exercise sciences could be attributed, at least ...

Inter-fractional portability of deep learning models for lung target tracking on cine imaging acquired in MRI-guided radiotherapy.

MRI-guided radiotherapy systems enable beam gating by tracking the target on planar, two-dimensional...

Using Vision Transformer for high robustness and generalization in predicting EGFR mutation status in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma is a common cause of cancer-related deaths worldwide, and accurate E...

Deep learning-radiomics integrated noninvasive detection of epidermal growth factor receptor mutations in non-small cell lung cancer patients.

This study focused on a novel strategy that combines deep learning and radiomics to predict epiderma...

Combining Digital and Molecular Approaches Using Health and Alternate Data Sources in a Next-Generation Surveillance System for Anticipating Outbreaks of Pandemic Potential.

Globally, millions of lives are impacted every year by infectious diseases outbreaks. Comprehensive ...