Latest AI and machine learning research in pulmonology for healthcare professionals.
Clinically manifested pneumonia associated with COVID-19 infection in cancer patients has been associated with worse prognosis. The prognostic significance of subclinical manifestations of pulmonary infiltration is poorly understood. To estimate the survival of cancer patients with signs of asymptomatic pneumonia detected by a multitarget artificial intelligence (AI) algorithm on chest computed to...
Exposure to chemical irritants in laboratory and medical environments poses significant health risks to workers, particularly in relation to asthma-like symptoms. Routine cleaning practices, which often involve the use of strong chemical agents to maintain hygienic settings, have been shown to contribute to respiratory issues. Laboratories, where chemicals such as hydrochloric acid and ammonia are...
The administration of gadolinium-based contrast agents (GBCAs) for acquiring contrast-enhanced T1-weighted magnetic resonance imaging (T1C MRI) is ass...
Diagnosis of asthma in primary care is challenged by a multistep pathway with variable adherence leading to significant misdiagnosis, late diagnosis a...
To evaluate the ability of a natural language processing system to automatically reconstruct the SOFA score from unstructured clinical notes in patien...
Chronic obstructive pulmonary disease (COPD) is the third leading cause of global mortality. Emerging evidence suggests the oral microbiome may contri...
Diffuse myocardial fibrosis contributes to adverse remodeling and heart failure progression in non-ischemic dilated cardiomyopathy (NIDCM). Quantitati...
To assess whether an artificial intelligence (AI) chest radiograph (CXR) tool could enhance lung cancer detection on primary care–referred CXRs in the...
Intracranial pressure (ICP) monitoring is commonly used in neuro-intensive care, but its utility may be limited by a suboptimal use. The brain pressur...
Intubation and mechanical ventilation are associated with high mortality. Accurately predicting which patients are at the highest risk of intubation c...
Cardiac fibrosis is a central pathological process in heart failure, yet the molecular mechanisms governing its spatial organization remain poorly def...
Preoperative cardiovascular (CV) risk stratification is essential in non-cardiac surgery, but conventional testing is frequently overused, increasing ...
Artificial intelligence (AI) models with medical images as input data are increasingly proposed to support clinical decisions in lung cancer screening...
We present a new method for lung pathology detection in blood plasma, including lung cancer staging. Raman spectroscopy uses inelastically scattered l...
Electronic health records (EHRs) provide a large source of data that can be used for research purposes. Extraction of information from unstructured cl...
Immunotherapy has improved outcomes in non-small cell lung cancer (NSCLC), but only a subset of patients achieves durable survival benefit. Convention...
Digital pathology enables large multi-centre studies of histological specimens, but differences in staining protocols and slide quality can compromise...
To develop machine-learning models for sleep stage classification, arousal detection, and respiratory event detection from polysomnography (PSG), and ...
Current circulating biomarkers for idiopathic pulmonary arterial hypertension (IPAH) lack specificity for preclinical detection and fail to capture th...
Low-dose computed tomography (LDCT) lung cancer screening has significantly enhanced early detection and patient survival rates in the population at r...