Pulmonology

A hybrid CNN-spectral architecture for non-contact respiratory rate estimation using multi-region optical-flow analysis.

Respiratory rate (RR) is a key indicator for assessing health conditions, yet noncontact measurement remains challenging due to motion artifacts, lighting variability, and skin-tone differences. This study presents a robust framework combining a custom convolutional neural network (CNN) with spectral analysis of optical-flow signals to estimate RR accurately across diverse population. Respiration-...

Generation of machine-learning derived cancer vulnerability indicator to determine the spatial burden of cancer outcomes.

BACKGROUND: Due to the difficulty of obtaining population-based individual-level data, ecological studies are often used to explore factors related to geographic variations in health outcomes. This study proposes a novel framework to identify area-level predictors of spatial variations in lung cancer outcomes and generate a lung cancer vulnerability index (LcVI) based on these predictors. METHODS:...

Aortic and Cardiac Structure From Routine CT Predict Cardiovascular Risk Beyond PREVENT and Coronary Calcium.

BACKGROUND: Cardiovascular disease prevention relies on accurate risk assessment; however, existing scores are imprecise. Routine imaging may be oppor...

The impact of chest computed tomography-defined emphysema on extrapulmonary metastases in patients with lung cancer.

Fusing data from CT deep learning, CT radiomics and peripheral blood immune profiles to diagnose lung cancer in a cohort of patients experiencing symptoms.

BACKGROUND: Lung cancer is the leading cause of cancer-related deaths. Diagnosis at late stages is common due to the largely non-specific nature of pr...

Histopathological diagnosis of Ovine Pulmonary Adenocarcinoma (OPA) based on ensemble model.

Automated Detection of Ventilator Asynchronies: A Clinical and Technological Perspective.

Patient-ventilator asynchrony is highly prevalent during invasive mechanical ventilation, yet its detection at the bedside remains limited. Convention...

Clinical History, Spirometry, and CT Features Can Predict Dyspnea in Smokers with and without Spirometry-Defined COPD.

ASO Visual Abstract: CT-Based Prediction of Visceral Pleural Invasion in Lung Adenocarcinoma ≤ 3 cm: Enhancing Deep Learning Specificity by Waiving Chest Wall Information.

Building an Extracorporeal Membrane Oxygenation Digital Twin Using High-Resolution Patient Data: An artificial intelligence model for virtual reality simulation.

OBJECTIVES: Extracorporeal membrane oxygenation (ECMO) is a life-saving therapy for severe cardiopulmonary failure, but structured training remains co...

Deep learning-based estimation of lung collapse in electrical impedance tomography: A simulation and phantom study.

Inhomogeneity of air volume distribution in the lungs of mechanically ventilated patients can lead to lung collapse and overdistention, increasing the...

Assessing mortality risk in pulmonary tuberculosis and severe malnutrition: development of the IIR marker via artificial intelligence.

Pneumonia detection from enhanced chest X-Ray images based on Double SGAN model.

Medical imaging plays a crucial role in clinical diagnosis, however, deep learning models often struggle with imbalanced datasets, which has a negativ...

Artificial Intelligence Could Predict Chest Tube Drainage Necessity for Spontaneous Pneumothorax.

Artificial intelligence (AI) is increasingly utilized in the medical field, primarily for diagnostic purposes. Although AI has demonstrated efficacy i...

Predicting cardiopulmonary exercise testing outcomes in congenital heart disease through multimodal data integration and geometric learning.

Cardiopulmonary exercise testing (CPET) provides a comprehensive assessment of functional capacity by measuring key physiological variables including ...

Development and Validation of a Frailty Risk Prediction Model for Preoperative Non-Small-Cell Lung Cancer Patients: A Cross-Sectional Study.

PURPOSE: Frailty is increasingly recognized as a predictor of poor surgical outcomes, yet its preoperative assessment in patients with non-small-cell ...

Bulk and single-cell transcriptomics for identification of potential diagnostic biomarkers associated with pulmonary arterial hypertension and integrated stress response and experimental validation.

BACKGROUND: Pulmonary arterial hypertension (PAH) is a lethal vascular disorder characterized by irreversible remodeling of the pulmonary arteries, bu...

Prediction of Symptomatic Radiation Pneumonitis in Lung Cancer Patients: A Radiomics and Dosiomics Machine Learning Approach Using the Prospective Multicenter RTOG 0617 and REQUITE Trials.

PURPOSE: Radiation-induced pneumonitis (RP) is a side effect after thoracic radiation therapy (RT). The ability to predict RP would facilitate treatme...

A multiscale theory framework predicts size- and ordering-dependent activity in Pt-Cu oxygen reduction reaction catalysts.

Optimizing the oxygen reduction reaction (ORR) performance of Pt-based alloy nanocatalysts requires a quantitative understanding of how catalytic acti...

Microbial community biomarkers can forecast methane production in full-scale anaerobic digesters.

Methane production from wastewater sludge via anaerobic digestion is a complex process and a disturbance in any one of the microbial stages can lead t...