Pulmonology

Deep learning-driven bacterial cytological profiling to determine antimicrobial mechanisms in .

Tuberculosis (TB), caused by , remains a significant global health threat, affecting an estimated 10...

Assessing the diagnostic accuracy of machine learning algorithms for identification of asthma in United States adults based on NHANES dataset.

Asthma diagnosis poses challenges due to underreporting of symptoms, misdiagnoses, and limitations i...

Forecasting the Incidence of Mumps Based on the Baidu Index and Environmental Data in Yunnan, China: Deep Learning Model Study.

BACKGROUND: Mumps is a viral respiratory disease characterized by facial swelling and transmitted th...

KL-DNAS: Knowledge Distillation-Based Latency Aware-Differentiable Architecture Search for Video Motion Magnification.

Video motion magnification is the task of making subtle minute motions visible. Many times subtle mo...

Explainable Classification of Benign-Malignant Pulmonary Nodules With Neural Networks and Information Bottleneck.

Computerized tomography (CT) is a clinically primary technique to differentiate benign-malignant pul...

Cross-ViT based benign and malignant classification of pulmonary nodules.

The benign and malignant discrimination of pulmonary nodules plays a very important role in diagnosi...

Development of a machine learning model related to explore the association between heavy metal exposure and alveolar bone loss among US adults utilizing SHAP: a study based on NHANES 2015-2018.

BACKGROUND: Alveolar bone loss (ABL) is common in modern society. Heavy metal exposure is usually co...

Panoramic radiographic features for machine learning based detection of mandibular third molar root and inferior alveolar canal contact.

This study uses machine learning (ML) to elucidate the contact relationship between the mandibular t...

Modeling the latent impacts of extreme floods on indoor mold spores in residential buildings: Application of machine learning algorithms.

Floods can severely impact the economy, environment and society. These impacts can be direct and ind...

[Artificial intelligence in paediatric pneumology - opportunities and unanswered questions].

Artificial intelligence (AI) is already being used in most medical disciplines, including paediatric...

Development and Evaluation of a Deep Learning-Based Pulmonary Hypertension Screening Algorithm Using a Digital Stethoscope.

BACKGROUND: Despite the poor outcomes related to the presence of pulmonary hypertension, it often go...

Unlocking the link: predicting cardiovascular disease risk with a focus on airflow obstruction using machine learning.

BACKGROUND: Respiratory diseases and Cardiovascular Diseases (CVD) often coexist, with airflow obstr...

Prediction of the Risk of Adverse Clinical Outcomes with Machine Learning Techniques in Patients with Noncommunicable Diseases.

Decision-making in chronic diseases guided by clinical decision support systems that use models incl...

Normative values for lung, bronchial sizes, and bronchus-artery ratios in chest CT scans: from infancy into young adulthood.

OBJECTIVE: To estimate the developmental trends of quantitative parameters obtained from chest compu...

Leveraging deep-learning and unconventional data for real-time surveillance, forecasting, and early warning of respiratory pathogens outbreak.

BACKGROUND: Controlling re-emerging outbreaks such as COVID-19 is a critical concern to global healt...

Automated Euler number of the alveolar capillary network based on deep learning segmentation with verification by stereological methods.

Diseases like bronchopulmonary dysplasia (BPD) affect the development of the pulmonary vasculature, ...

Exploring the assessment of post-cardiac valve surgery pulmonary complication risks through the integration of wearable continuous physiological and clinical data.

BACKGROUND: Postoperative pulmonary complications (PPCs) following cardiac valvular surgery are char...

Automated recognition and segmentation of lung cancer cytological images based on deep learning.

Compared with histological examination of lung cancer, cytology is less invasive and provides better...

A Machine Learning Model Score Predicts Advanced Fibrosis and Cirrhosis in Indeterminate FIB-4 Patients.

Tumor Cellularity Assessment Using Artificial Intelligence Trained on Immunohistochemistry-Restained Slides Improves Selection of Lung Adenocarcinoma Samples for Molecular Testing.

Tumor cellularity (TC) in lung adenocarcinoma slides submitted for molecular testing is important in...

Deep learning and machine learning in CT-based COPD diagnosis: Systematic review and meta-analysis.

BACKGROUND: With advancements in medical technology and science, chronic obstructive pulmonary disea...