Pulmonology

Using artificial intelligence to identify characteristics associated with clinical and economic outcomes in MASH (FOCUS-MASH).

BACKGROUND: Heterogeneity in the disease characteristics of metabolic dysfunction-associated steatohepatitis (MASH) complicates efforts to identify individuals with high unmet need. OBJECTIVE: We used artificial intelligence (AI) phenotyping to identify factors associated with rapid fibrosis progression, long-term clinical outcomes, and high healthcare costs. DESIGN: In this retrospective cohort s...

Integrative profiling of senescence-associated cells and genes identifies UGT1A7 as a prognostic and therapeutic target in Lung squamous cell carcinoma.

Lung Squamous Cell Carcinoma (LUSC), a common subtype of non-small cell lung cancer, primarily occurs in elderly individuals and is closely linked to senescence-related biological processes. Meanwhile, senescence reshapes the tumor microenvironment by promoting immune suppression and angiogenesis, and its underlying mechanisms remain unclear. Here, we identified three senescence-related molecular ...

Cardio-respiratory deep learning model to predict hospital admission from emergency department electrocardiogram images and respiration videos: a prospective study.

BACKGROUND: Early prediction of hospital admission at the emergency department (ED) triage can improve patient flow and resource allocation. Most exis...

Air quality and health implications of exposure to ultrafine particle pollution.

AIMS: Ultrafine particles (UFPs) smaller than 100 nm are ubiquitous in polluted air. Although they carry little mass, UFPs have a large exposure surfa...

Virus infections and cancers: from mechanisms to therapeutics.

Viral infections are a major contributor to global cancer incidence and mortality. However, integrative reviews that connect viral classification, car...

Risk prediction of non-small cell lung cancer in patients with pulmonary nodules: a single-center cohort study based on six machine learning algorithms.

OBJECTIVE: Lung cancer is a major global public health concern. Non-small cell lung cancer (NSCLC), the most common subtype, has drawn increasing atte...

Data-scarce transfer learning fusion for positron emission tomography and computed tomography guided lung biopsy.

OBJECTIVES: We developed a transfer learning-based multimodal fusion deep learning model integrating positron emission tomography/computed tomography ...

Precision treatment of COPD based on novel imaging phenotypes: a treatable traits approach.

Chronic obstructive pulmonary disease (COPD) is a heterogeneous syndrome. Spirometry, while diagnostic, inadequately characterizes disease complexity....

Risk prediction for lung cancer screening: a systematic review and meta-regression.

BACKGROUND: Lung cancer (LC) remains the deadliest cancer, often diagnosed at advanced stages. Screening reduces mortality in high-risk individuals. E...

Prediction of PD-L1 expression in nonsmall cell lung cancer using artificial intelligence models based on radiomics: a systematic review and meta-analysis.

BACKGROUND: Since 1992, the incidence of lung cancer has shown an overall downward trend, with survival rates significantly improving in recent years ...

Explainable machine learning for the early differentiation of pediatric bronchopneumonia using routine laboratory parameters.

OBJECTIVE: Early differentiation of pediatric acute respiratory infections in outpatient and emergency settings is often hindered by nonspecific clini...

Air quality index prediction using machine learning regression models: A comparative analysis.

Air plays a vital role in human life, and poor air quality can lead to respiratory infections. Given the significant impact of air quality on people's...

Dental image analysis and surgical decision support using modified generative adversarial networks.

BACKGROUND: Several clinical issues have remained in dental care and risk estimation because of the insufficient integration of multimodal features, t...

Identifying the Presence and Characteristics of Mid-Myocardial and Epicardial Fibrosis From Intracardiac Electrograms in Patients Undergoing Ventricular Arrhythmia Ablation Using a Transformer-Based Self-Supervised Classifier.

BACKGROUND: Catheter ablation is an essential tool for ventricular arrhythmia management, yet sustained procedural success is hindered by the limited ...

Utility of E-Nose in Paediatric Respiratory Diseases Using Machine Learning Approach: A Pilot Study.

To assess the feasibility of an electronic nose (e-nose) for volatile organic compounds (VOCs) to classify respiratory diseases and establish a protoc...

Quantitative Cerebrovascular Analysis for Improved Prediction of Post-Stroke Complications.

Endovascular thrombectomy (EVT) has transformed the treatment of acute ischemic stroke (AIS). However, a substantial proportion of AIS patients experi...

Single-cell and Spatial Transcriptomic Profiling Reveal that LAPTM5-mediated Ferroptosis in Macrophages Induces Fibroblast Dysfunction and Amplifies Periodontal Inflammation.

Periodontitis represents a persistent inflammatory condition marked by gradual damage to the gingival connective tissues and alveolar bone. Programmed...

From single targets to circuits diversified discovery and development strategies towards new paradigms for non-opioid analgesics.

The long-term use of opioids for analgesia is associated with serious adverse effects such as addiction and respiratory depression, as well as a poten...

Empowering clinical trial design with agentic intelligence and real-world data.

Clinical trial design (CTD) is a time-consuming process that requires substantial domain expertise. Large-scale real-world data (RWD), such as electro...

HyCANet: a hybrid convolutional-attention network with cross-attention fusion for lung cancer histopathological classification.

Histopathology interpretation of lung cancer involves careful examination of tissue morphology, especially differentiating benign lung tissue, adenoca...