Pulmonology

The Montafon proposal: New insights and emerging concepts in pulmonary rehabilitation.

Background Pulmonary rehabilitation (PR) is beneficial, yet outcome assessment remains inconsistent. A multidisciplinary D-A-CH working group reviewed evidence, introduced new measures, and explored emerging PR concepts. Summary The meeting emphasized patient-reported (PROMs) and clinician-reported (CROMs) outcome measures. A key focus was the minimal clinically important difference (MCID), a wide...

Automated daily adaptation for breast cancer radiotherapy: benefits of deep learning-driven dose prediction workflow for CBCT-based adaptation.

Objective Daily anatomical variations can jeopardize the quality of modern radiotherapy (RT). Adaptive radiotherapy (ART) aims to address this by adjusting treatment plans according to the patient's daily anatomy. However, as implementation of ART is currently time-consuming, laborious, and expensive, its routine clinical use remains limited. In this study, we investigate the feasibility of us...

Comparison of Left Ventricular Ejection Fraction Among 18F-FDG Dual-Gated PET/CT, Single-Gated PET/MRI, and Cardiac MRI.

Left ventricular ejection fraction (LVEF) is a critical parameter in the evaluation of cardiac function, and its measurement can guide treatment decis...

A comprehensive analysis of retrieving optically inactive indicators from multi-level remote sensing product(s) in Irish waters using data science techniques.

The present research was carried out to retrieve dissolved oxygen (DOX) using the Copernicus Marine Services products from the Irish transitional and ...

Plasma proteomic profiling with machine learning identifies immunometabolic perturbations associated with smoking and smoking cessation.

Cigarette smoking is the leading modifiable risk factor for chronic obstructive pulmonary disease (COPD) and is associated with systemic molecular alt...

Biosphere expansion drives Earth's secular oxygenation while tectonics modulate oxygen variability revealed by machine learning.

The rise of atmospheric oxygen fundamentally transformed Earth's surface environment and enabled the evolution of complex life. However, the processes...

Interpretable Multi-Modality Consensus QSAR Framework: Integrating Machine and Deep Learning for Enhanced Multi-Endpoint Toxicity Assessment.

Accurate toxicity assessment is essential for chemical safety, but experimental testing is costly, slow, and ethically constrained, motivating the ado...

Combining computed tomography radiomics and clinical features to predict lymph node metastasis in patients with lung cancer.

BACKGROUND: Accurate preoperative assessment of lymph node metastasis (LNM) is crucial for treatment planning and prognostic stratification in patient...

Artificial Intelligence in Predicting Surgical Problems and Postoperative Morbidity in Mandibular Third Molar Extractions.

INTRODUCTION: Mandibular third molar (MTM) extractions are among the most frequent oral surgical procedures, often associated with variable surgical d...

Deep learning-based identification of chronic pulmonary embolism on CTPA: a regional lung analysis using multiplanar MIP images.

OBJECTIVE: Chronic pulmonary embolism (CPE) and chronic thromboembolic pulmonary hypertension (CTEPH) are challenging to diagnose, with delayed detect...

CT acquisition protocols in lung cancer screening: implications for guideline development from a worldwide survey.

OBJECTIVES: To assess the currently applied CT image acquisition protocols in lung cancer screening (LCS) and thereby fill a knowledge gap to support ...

Current and future contributions of AI to pulmonary function test interpretation, diagnostic approaches, and predictions of disease progression.

INTRODUCTION: Artificial intelligence (AI) methods - including machine learning, deep learning, and explainable AI - are increasingly applied to pulmo...

On Demographic Group Fairness Guarantees in Deep Learning.

We present a comprehensive theoretical framework analyzing the relationship between data distributions and fairness guarantees in equitable deep learn...

Assessing interstitial fibrosis and tubular atrophy in kidney biopsies artificial intelligence versus humans.

PURPOSE OF REVIEW: The degree to which computerized methods, such as artificial intelligence (AI), will aid in the assessment of kidney histopathology...

Med-ViX-Ray: Enhancing explainable chest X-ray analysis with clinical knowledge graphs.

BACKGROUND AND OBJECTIVE: Deep learning has achieved remarkable success in chest x-ray interpretation, yet most models remain black boxes, producing a...

Explainable machine learning for postoperative respiratory failure prediction in open-heart surgery patients - a study based on the MIMIC-IV database.

BACKGROUND: Postoperative respiratory failure (PRF) is a severe complication after open-heart surgery, associated with increased mortality and prolong...

Integrative Approaches in Lung Cancer Diagnosis: Bridging Molecular Biomarkers and AI Driven Imaging.

Though critical, traditional diagnostic approaches such as X-ray, CT scans, bronchoscopy and tissue biopsy don't reliably detect lung cancer at early ...

Bone tuberculosis: molecular pathogenesis, diagnostic advances, therapeutic challenges, and emerging strategies for effective management.

A review of artificial intelligence-based research on chronic obstructive pulmonary disease.

In recent years, with the rapid development of artificial intelligence (AI), Chronic Obstructive Pulmonary Disease (COPD), one of the world's three ma...

Machine learning-based proteogenomic data modeling identifies circulating plasma biomarkers for early detection of lung cancer.

BACKGROUND: Genetic aberrations are among the critical driving factors of lung cancer. Importantly, the impact of genetic variations on proteomic dysr...