Pulmonology

Identifying health risk determinants and molecular targets in patients with idiopathic pulmonary fibrosis via combined differential and weighted gene co-expression analysis.

INTRODUCTION: Idiopathic pulmonary fibrosis (IPF) is a rare but debilitating lung disease characterized by excessive fibrotic tissue accumulation, primarily affecting individuals over 50 years of age. Early diagnosis is challenging, and without intervention, the prognosis remains poor. Understanding the molecular mechanisms underlying IPF pathogenesis is crucial for identifying diagnostic markers ...

Advancing lung cancer diagnosis: Combining 3D auto-encoders and attention mechanisms for CT scan analysis.

ObjectiveThe goal of this study is to assess the effectiveness of a hybrid deep learning model that combines 3D Auto-encoders with attention mechanisms to detect lung cancer early from CT scan images. The study aims to improve diagnostic accuracy, sensitivity, and specificity by focusing on key features in the scans.Materials and methodsA hybrid model was developed that combines feature extraction...

Multiplex Detection and Quantification of Virus Co-Infections Using Label-free Surface-Enhanced Raman Spectroscopy and Deep Learning Algorithms.

Multiple respiratory viruses can concurrently or sequentially infect the respiratory tract, making their identification crucial for diagnosis, treatme...

Accuracy of artificial intelligence algorithms in predicting acute respiratory distress syndrome: a systematic review and meta-analysis.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a serious threat to human life. Hence, early and accurate diagnosis and treatment are crucia...

Identification of patient demographic, clinical, and SARS-CoV-2 genomic factors associated with severe COVID-19 using supervised machine learning: a retrospective multicenter study.

BACKGROUND: Drivers of COVID-19 severity are multifactorial and include multidimensional and potentially interacting factors encompassing viral determ...

Non-experimental rapid identification of lower respiratory tract infections in patients with chronic obstructive pulmonary disease using multi-label learning.

BACKGROUND AND OBJECTIVE: Microbiological culture is a standard diagnostic test that takes a long time to identify lower respiratory tract infections ...

Predicting the effectiveness of chemotherapy treatment in lung cancer utilizing artificial intelligence-supported serum N-glycome analysis.

An efficient novel approach is introduced to predict the effectiveness of chemotherapy treatment in lung cancer by monitoring the serum N-glycome of p...

Artificial intelligence for diagnosis and predictive biomarkers in Non-Small cell lung cancer Patients: New promises but also new hurdles for the pathologist.

The rapid development of artificial intelligence (AI) based tools in pathology laboratories has brought forward unlimited opportunities for pathologis...

Enhancing Diagnostic Accuracy of Lung Nodules in Chest Computed Tomography Using Artificial Intelligence: Retrospective Analysis.

BACKGROUND: Uncertainty in the diagnosis of lung nodules is a challenge for both patients and physicians. Artificial intelligence (AI) systems are inc...

Deep learning-based algorithm for classifying high-resolution computed tomography features in coal workers' pneumoconiosis.

BACKGROUND: Coal workers' pneumoconiosis is a chronic occupational lung disease with considerable pulmonary complications, including irreversible lung...

Impact of Deep Learning 3D CT Super-Resolution on AI-Based Pulmonary Nodule Characterization.

BACKGROUND/OBJECTIVES: Correct pulmonary nodule volumetry and categorization is paramount for accurate diagnosis in lung cancer screening programs. CT...

Classification of CT scan and X-ray dataset based on deep learning and particle swarm optimization.

In 2019, the novel coronavirus swept the world, exposing the monitoring and early warning problems of the medical system. Computer-aided diagnosis mod...

Using machine learning to forecast peak health care service demand in real-time during the 2022-23 winter season: A pilot in England, UK.

During winter months, there is increased pressure on health care systems in temperature climates due to seasonal increases in respiratory illnesses. P...

Waveform characteristics in thoracic paravertebral space: a prospective observational study.

BACKGROUND: With increased use of thoracic paravertebral block (TPVB) in thoracic surgery, many faced the challenge of locating the thoracic paraverte...

Feature-targeted deep learning framework for pulmonary tumorous Cone-beam CT (CBCT) enhancement with multi-task customized perceptual loss and feature-guided CycleGAN.

Thoracic Cone-beam computed tomography (CBCT) is routinely collected during image-guided radiation therapy (IGRT) to provide updated patient anatomy i...

Brachytherapy Seed Placement by Robotic Bronchoscopy with Cone Beam Computed Tomography Guidance for Peripheral Lung Cancer: A Human Cadaveric Feasibility Pilot.

PURPOSE: This study evaluates the feasibility of using robotic-assisted bronchoscopy with cone beam computed tomography (RB-CBCT) platform to perform ...

NAVT-net neuron attention visual taylor network for lung cancer detection using CT images.

Lung Cancer is regarded as a common fatal disease affecting humans throughout the entire world. Early diagnosis is vital to save the patient's life an...

Automated mechanical ventilator design and analysis using neural network.

Mechanical ventilation is the process through which breathing support is provided to patients who face inconvenience during respiration. During the pa...

Machine-learning model based on ultrasomics for non-invasive evaluation of fibrosis in IgA nephropathy.

OBJECTIVES: To develop and validate an ultrasomics-based machine-learning (ML) model for non-invasive assessment of interstitial fibrosis and tubular ...

Machine learning models for preventative mobile health asthma control.

INTRODUCTION: Asthma attacks are set off by triggers such as pollutants from the environment, respiratory viruses, physical activity and allergens. Th...