Pulmonology

Peripheral blood mononuclear cell DNA methylation signatures guide surgical decision-making in indeterminate pulmonary nodules.

BACKGROUND: Distinguishing malignant from benign pulmonary nodules remained a significant clinical challenge. Given the involvement of DNA methylation in anti-tumor immunity, we aimed to investigated whether DNA methylation patterns in peripheral blood mononuclear cells (PBMCs) could serve as non-invasive biomarkers for pulmonary nodule classification. METHODS: Genome-wide DNA methylation profilin...

Integration of Single-Cell RNA Sequencing and Machine Learning to Identify and Validate Prognostic Genes With Lymph Node Metastasis and Immune Cell Signatures in Lung Adenocarcinoma.

The poor prognosis of lung adenocarcinoma (LUAD) remains unimproved. This study aimed to identify lymph node metastasis (LNM)-related and cellular immunity-related prognostic genes in LUAD and propose novel strategies to improve its prognosis. LUAD-related datasets were obtained from public databases. Prognostic genes and a prognostic model were obtained through various bioinformatics analyzes, an...

Exploratory association between multimodal AI-derived digital biomarkers and in-hospital mortality in adult patients with pneumonia: A proof-of-concept study.

Pneumonia remains a leading cause of in-hospital mortality worldwide. Current prognostic tools such as the IDSA/ATS severity score have meaningful lim...

A dynamic proteomic signature for the prediction of lung Cancer: a longitudinal analysis in the UK Biobank cohort.

BACKGROUND: To understand the molecularly obscure pre-diagnostic phase of lung cancer, we mapped the temporal evolution of the plasma proteome for new...

A novel serum metabolite classifier for identifying Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) integrating metabolomics and machine learning.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) presents a growing global health burden, while reliable non-invasive biom...

Artificial intelligence-assisted risk prediction of postoperative pulmonary complications in non-small cell lung cancer surgery.

BACKGROUND: Pulmonary complications are the most frequent adverse events following surgery for non-small cell lung cancer (NSCLC), influencing both sh...

Retinal imaging and supervised learning predict hospitalizations, kidney, and heart-lung damage in sickle cell disease.

Sickle cell disease (SCD) is a single-gene illness which causes painful vaso-occlusion, debilitating organ damage, and early mortality. Its clinical c...

Quantitative CT Measurements of Interstitial Lung Disease: Same-Day Variability Between Two Vendors-A Prospective Study.

BACKGROUND. Clinical application of quantitative CT (QCT) measurements of interstitial lung disease (ILD) for longitudinal monitoring of disease progr...

Repurposing Clinical Candidates for Nipah and Hendra Viruses.

Nipah virus (NiV) and Hendra virus (HeV) are bat-borne zoonotic paramyxoviruses that cause severe and often fatal respiratory and neurological disease...

[Artificial intelligence-assisted diagnostics in the pathology of internal and oncological diseases].

BACKGROUND: Artificial intelligence (AI) is increasingly being implemented in digital pathology to support the tissue classification, cell detection, ...

Clinical validation and implementation of mSTOP, a machine learning-based, longitudinal prediction model for the early identification of non-small cell lung cancer patients who not benefit from immune checkpoint inhibitor treatment.

OBJECTIVES: There has been a lot of interest in the field of laboratory medicine regarding the use of machine learning (ML)-based prediction models. T...

Perioperative hypoxaemia early warning based on high-frequency waveform fusion and deep learning.

The accurate prediction of impending intraoperative hypoxaemic events is paramount for patient safety. Current models relying on structural parameters...

Molecular characterisation of progressive pulmonary sarcoidosis: protocol for a longitudinal multi-centre study to develop peripheral blood circulating biomarkers for predicting pulmonary sarcoidosis progression.

INTRODUCTION: Sarcoidosis is a heterogeneous granulomatous disease with highly variable clinical trajectories, yet no validated biomarkers exist to di...

Hybrid deep learning and YAMNet features for asthma diagnosis from respiratory sounds.

A prompt and precise diagnosis is necessary to lessen the worldwide burden of asthma, a common chronic respiratory condition. Spirometry is one of the...

An agentic framework for autonomous scientific discovery in cancer pathology.

Artificial intelligence has advanced cancer pathology, but many systems still depend on hand-crafted features, are hard to explain and rely on fragmen...

The role of mechanical power in lung ventilation for the prevention of ventilator-induced lung injury: a narrative review.

Ventilator-induced lung injury continues to limit outcomes in patients with acute respiratory failure despite established lung-protective strategies.M...

A cross-sectional protocol for experimental tongue high-density surface electromyography to detect and classify radiation-associated hypoglossal neuropathy.

BACKGROUND: Hypoglossal neuropathy is the most common lower cranial neuropathy detected as a delayed sequelae of Human Papillomavirus (HPV) -driven or...

The effects of fatigue on the relation between ocular pursuit and interceptive performance in soccer experts.

Accuracy and duration of ocular pursuit of a target object have been linked to interceptive performance. Yet, previous assessments have not examined t...

DFCNet: A Precise Detection Approach for Obstructive Sleep Apnea-Hypopnea Events Using Airflow and Respiratory Effort Signals.

OBJECTIVE: The diagnosis of Sleep Apnea-Hypopnea Syndrome (SAHS) holds significant importance for assessing sleep quality and treating sleep disorders...

Data-Efficient Language Model for Assessing Pulmonary Embolism Diagnostic Certainty From Radiology Reports: Model Development and Validation Study.

BACKGROUND: Computed tomography pulmonary angiography (CTPA) is the standard imaging modality for diagnosing pulmonary embolism (PE), but diagnostic u...