Pulmonology

Malignancy risk stratification for pulmonary nodules: comparing a deep learning approach to multiparametric statistical models in different disease groups.

OBJECTIVES: Incidentally detected pulmonary nodules present a challenge in clinical routine with demand for reliable support systems for risk classification. We aimed to evaluate the performance of the lung-cancer-prediction-convolutional-neural-network (LCP-CNN), a deep learning-based approach, in comparison to multiparametric statistical methods (Brock model and Lung-RADS®) for risk classificati...

Efficacy of a deep learning system for automatic analysis of the comprehensive spatial relationship between the mandibular third molar and inferior alveolar canal on panoramic radiographs.

OBJECTIVE: To develop and evaluate a deep learning (DL) system for predicting the contact and relative position relationships between the mandibular third molar (M3) and inferior alveolar canal (IAC) using panoramic radiographs (PRs) for preoperative assessment of patients for M3 surgery.

Attention-guided CenterNet deep learning approach for lung cancer detection.

Lung cancer remains a significant health concern worldwide, prompting ongoing research efforts to enhance early detection and diagnosis. Prior studies...

Fibrosis and inflammatory activity diagnosis of chronic hepatitis C based on extreme learning machine.

The traditional diagnosis of chronic hepatitis C usually relies on liver biopsy. Diagnosing chronic hepatitis C based on serum indices provides a non-...

Employing a low-code machine learning approach to predict in-hospital mortality and length of stay in patients with community-acquired pneumonia.

Community-acquired pneumonia (CAP) is associated with high mortality rates and often results in prolonged hospital stays. The potential of machine lea...

Tumor detection on bronchoscopic images by unsupervised learning.

The diagnosis and early identification of intratracheal tumors relies on the experience of the operators and the specialists. Operations by physicians...

Deciphering the cellular and molecular landscape of pulmonary fibrosis through single-cell sequencing and machine learning.

Pulmonary fibrosis is characterized by progressive lung scarring, leading to a decline in lung function and an increase in morbidity and mortality. Th...

Noninvasive diagnosis of significant liver fibrosis in patients with chronic hepatitis B using nomogram and machine learning models.

This study aims to construct and validate noninvasive diagnosis models for evaluating significant liver fibrosis in patients with chronic hepatitis B ...

BCNet: Bronchus Classification via Structure Guided Representation Learning.

CT-based bronchial tree analysis is a key step for the diagnosis of lung and airway diseases. However, the topology of bronchial trees varies across i...

Identification of key gene signatures for predicting chemo-immunotherapy efficacy in extensive-stage small-cell lung cancer using machine learning.

OBJECTIVES: The lack of definitive biomarkers presents a significant challenge for chemo-immunotherapy in extensive-stage small-cell lung cancer (ES-S...

Machine learning identifies remodeling patterns in human lung extracellular matrix.

Organ function depends on the three-dimensional integrity of the extracellular matrix (ECM). The structure resulting from the location and association...

Exploring machine learning tools in a retrospective case-study of patients with metastatic non-small cell lung cancer treated with first-line immunotherapy: A feasibility single-centre experience.

BACKGROUND: Artificial intelligence (AI) models are emerging as promising tools to identify predictive features among data coming from health records....

EC and EC of Remifentanil for Inhibiting Bronchoscopy Responses in Elderly Patients During Fiberoptic Bronchoscopy Under Ciprofol Sedation: An Up-and-Down Sequential Allocation Trial.

BACKGROUND: Opioids are used to suppress cough during fiberoptic bronchoscopy (FOB). However, evidence regarding the optimal dose of remifentanil duri...

Construction of geriatric hypoalbuminemia predicting model for hypoalbuminemia patients with and without pneumonia and explainability analysis.

BACKGROUND AND OBJECTIVES: Pneumonia portrays a critical health concern in geriatrics. Geriatric pneumonia can lead to changes on other complications,...

Characteristics and outcomes of pulmonary barotrauma in patients with COVID-19 ARDS: A retrospective observational study.

INTRODUCTION: Pulmonary barotrauma in coronavirus disease-2019 (COVID-19) acute respiratory distress syndrome (ARDS) carries high risk of mortality. W...

Assessment of Craniofacial Growth Pattern Relative to Respiratory Mandibular Movement and Sleep Characteristics: A Pilot Study.

OBJECTIVES:  The primary objective was to evaluate the influence of sagittal skeletal pattern on mandibular movement (MM) during sleep in growing orth...

Towards safe and reliable deep learning for lung nodule malignancy estimation using out-of-distribution detection.

Artificial Intelligence (AI) models may fail or suffer from reduced performance when applied to unseen data that differs from the training data distri...

Machine learning-based forecast of Helmet-CPAP therapy failure in Acute Respiratory Distress Syndrome patients.

BACKGROUND AND OBJECTIVE: Helmet-Continuous Positive Airway Pressure (H-CPAP) is a non-invasive respiratory support that is used for the treatment of ...

An artificial intelligence application to predict prolonged dependence on mechanical ventilation among patients with critical orthopaedic trauma: an establishment and validation study.

BACKGROUND: Prolonged dependence on mechanical ventilation is a common occurrence in clinical ICU patients and presents significant challenges for pat...

Sub-millimeter fiberscopic robot with integrated maneuvering, imaging, and biomedical operation abilities.

Small-scale continuum robots hold promise for interventional diagnosis and treatment, yet existing models struggle to achieve small size, precise stee...