Pulmonology

Spatial and multi-omics transcriptomic dissects platinum resistance in lung adenocarcinoma: a five-gene predictive model with tumor microenvironment dynamics.

The scarcity of reliable biomarkers and predictive models for platinum resistance in lung adenocarcinoma (LUAD) poses a significant clinical challenge. This study endeavors to identify molecular subtypes related to platinum resistance and construct a robust predictive model through multi-omics techniques. We performed integrative analysis of public datasets using advanced bioinformatics strategies...

Multi-objective optimization of oxygen transfer and hydrodynamic shear in dual-impeller stirred tanks via integrated computational fluid dynamics and machine learning framework.

Optimizing the structure of stirred bioreactors is crucial to improve the efficiency of biomanufacturing. This study proposes an intelligent design framework integrating computational fluid dynamics (CFD), machine learning (ML), and the non-dominated sorting genetic algorithm II (NSGA-II) to co-optimize the oxygenation and shear performance of a dual-impeller stirred tank. Initially, a parameteriz...

Dual Framework for Classification and Detection of Third Molar Impaction in Panoramic Radiographs.

BACKGROUND: The surgical extraction of impacted mandibular third molars present significant clinical challenges, where accurate preoperative assessmen...

Current perspectives in cardiogenic shock.

Cardiogenic shock (CS) remains a leading cause of death in intensive cardiac care. Outcomes are limited by delayed recognition of hypoperfusion, heter...

Integrating multi-source data and machine learning to Decipher the psoriasis-COPD comorbidity.

Update on Non-Biological and RNA-Based Therapeutics in Chronic Inflammatory Diseases: Precision Medicine Through Small Molecules.

In the last decades, critical advancements in research technology and knowledge on disease mechanisms steered therapeutic approaches for chronic infla...

Application of machine learning for the diagnosis and prognosis of sepsis-induced acute respiratory distress syndrome: a systematic review and meta-analysis.

Machine learning model predicts prognosis in SARS-CoV-2-infected autoimmune encephalitis patients.

OBJECTIVE: To assess the neurological prognosis of patients with autoimmune encephalitis (AE) after severe acute respiratory syndrome coronavirus 2 (S...

From Ageing Clocks to Organ Networks: Biological Age-Driven Organ Asynchrony and Inter-organ Interactions Shaping Mortality Risk.

Ageing is a multidimensional and heterogeneous process that progresses asynchronously across organ systems. Advances in multi-omics technologies have ...

Machine Learning Models for Posttransplant Lymphoproliferative Disorder (PTLD) Risk Prediction in Thoracic Transplantation.

Posttransplant lymphoproliferative disorder (PTLD) is the second most common malignancy in thoracic transplant recipients and is associated with poor ...

Interpretable deep learning model of circulating genomics for quantitative survival prediction in advanced non-small cell lung cancer.

PURPOSE: Accurate quantitative survival prediction in advanced non-small cell lung cancer (NSCLC) remains an unmet clinical need. While liquid biopsy ...

Few-Shot Pulmonary Vessel Segmentation based on Tubular-Aware Prompt-Tuning.

Segmentation of the pulmonary vessel from computed tomography (CT) images plays a crucial role in the diagnosis and treatment of various lung diseases...

A cascaded CNN-LSTM framework for quantifying respiratory motion from surface electromyographic signals.

OBJECTIVE: Surface electromyographic (sEMG) signals of the diaphragm provide a valuable physiological signal for real-time respiratory monitoring, par...

Intraoperative biopsy imaging of lung cancer risk.

BACKGROUND: Before surgical resection of lung tumor, intraoperative biopsy is needed for cancer diagnosis, while current techniques that guide biopsy ...

CT-based radiomics for predicting PD-L1 expression status in non-small cell lung cancer using a hybrid machine learning model.

PURPOSE: Programmed cell death ligand-1 (PD-L1) is a key prognostic and predictive biomarker for immunotherapy in non-small cell lung cancer (NSCLC). ...

The effect of artificial intelligence-assisted pulmonary rehabilitation on exercise capacity: A systematic review and meta-analysis.

INTRODUCTION: Artificial intelligence (AI) technologies are increasingly being integrated into pulmonary rehabilitation (PR) to improve individualizat...

[Radiological diagnosis of interstitial lung disease].

Diffuse interstitial lung diseases (ILDs) represent a complex and heterogeneous group of pulmonary disorders, requiring a structured, rigorous, and in...

Factors influencing long-term outcomes in lung transplantation: effective monitoring and comprehensive intervention.

PURPOSE OF REVIEW: Achieving long-term survival after lung transplantation remains a major challenge. Outcome determinants have expanded beyond pathop...

Synergistic impact of Gram-negative bacterial co-infection on invasive pulmonary aspergillosis in non-neutropenic patients: a machine learning-based risk stratification approach.

BACKGROUND: Invasive pulmonary aspergillosis (IPA) is increasingly recognized in non-neutropenic patients, where coexisting bacterial infections, part...

Auto-LSN: fully automated liver surface nodularity quantification in CT based on deep learning for the evaluation of advanced chronic liver disease.

OBJECTIVES: Liver surface nodularity (LSN) is a recognized non-invasive biomarker of cirrhosis. This study introduces auto-LSN, an artificial intellig...