Pulmonology

Deep learning for malignancy and tumor origin prediction using cytology or histopathology whole slide images.

Pleural and ascitic cytology is essential for diagnosing metastatic cancer and predicting tumor origin, yet microscopic observation alone often leads to low accuracy and observer variability. Although deep learning shows great potential in pathology, its use in pleural and ascitic cytology remains limited. We present a data-efficient deep learning framework (MAMILE-UNI) that directly detects malig...

Prognostic value of deep learning-based coronary artery calcium score and quantitative pneumonia burden in patients hospitalized with COVID-19.

CT-based radiomics nomogram for preoperative prediction of Ki-67 in lung neuroendocrine neoplasms: a multicenter study.

OBJECTIVE: Lung neuroendocrine neoplasms (L-NENs) are increasingly recognized, yet reliable preoperative assessment of the Ki-67 proliferation index r...

Letter to the editor: "A risk-adjusted length of stay to evaluate severe community-acquired pneumonia (sCAP) outcomes: a machine learning analysis of 16,985 ICU admissions".

'See' through the surface: surface-derived three-dimensional AI-driven real-time imaging solution for intra-treatment image guidance.

Respiratory motion is a long-standing challenge for lung stereotactic body radiotherapy (SBRT), particularly for centrally located lung tumors where i...

Recapitulating lung cancer metastasis in vitro: Advances in organoid models and challenges in clinical translation (Review).

Lung cancer remains a significant global health challenge, with metastatic progression being the leading driver of mortality. Organoid technology prov...

From Tissue Archives to Liquid Biopsy: Transfer Learning for MicroRNA-Based Lung Cancer Diagnosis.

Serum microRNA-based liquid biopsy holds a great application prospect in noninvasive lung cancer diagnosis. However, building an efficient serum-based...

Multimodal data-driven multitask learning for enhanced identification and classification of chronic obstructive pulmonary disease: a retrospective study.

BACKGROUND: Chronic obstructive pulmonary disease (COPD), the third leading cause of death worldwide, demands prompt and precise identification and ph...

Machine Learning Approach Enables Highly Accurate Identification of At-Risk Metabolic Dysfunction-Associated Steatohepatitis.

AIM: At-risk metabolic dysfunction-associated steatohepatitis (MASH), characterized by significant activity and fibrosis, increases the risk of liver ...

Improved screening for pulmonary Kaposi sarcoma in a low-resource setting.

OBJECTIVE: The lung is commonly involved in advanced Kaposi sarcoma (KS) but diagnosis of pulmonary KS in low-resource settings is difficult. Clinical...

Reproducing real-world clinical prediction models using the DIVE platform: A comparative validation study across three chronic diseases.

OBJECTIVES: The aim of this analysis is to evaluate the performance and reproducibility of the Python-based Data Insight Validation Engine (DIVE), a m...

An Integrated Deep Learning Framework Leveraging NASNet and Vision Transformer with MixProcessing for Accurate and Precise Diagnosis of Lung Diseases.

Lung diseases such as pneumonia, tuberculosis, COVID-19, and lung cancer remain significant global health challenges that demand rapid and accurate di...

Effective lung nodule segmentation and classification by employing a SPPUNet model and global context attention-based InceptionV3.

Lung nodules (LNs) detection using computer tomography (CT) images is essential to reduce the mortality of lung cancer (LC). The complex three-dimensi...

Lung scintigraphy for the diagnosis of acute pulmonary embolism.

Pulmonary embolism (PE) remains a major diagnostic challenge due to its potentially life-threatening nature and the clinical burden associated with an...

Fully automatic AI diagnosis of alveolar bone defect in anterior teeth on CBCT images.

OBJECTIVE: To develop a fully automatic artificial intelligence (AI) system for diagnosing alveolar bone defects (ABDs) in anterior teeth on cone-beam...

Deep Learning-Based Prediction of Cardiopulmonary Disease in Retinal Images of Premature Infants.

IMPORTANCE: Bronchopulmonary dysplasia (BPD) and pulmonary hypertension (PH) are leading causes of morbidity and mortality in premature infants. OBJEC...

Immune Checkpoint Activity and Prognostic Roles of TNFRSF8, CD160, and TNFSF9 in Primary and Brain Metastatic NSCLC.

Here, we utilized advanced bioinformatics approaches alongside experimental validation to identify key prognostic biomarkers and potential immune chec...

Classification of industrial chemicals for respiratory chemosensory irritation using the TRPV1-expressing neuronal SH-SY5Y cell model and machine learning.

Artificial intelligence in idiopathic pulmonary fibrosis: advances, challenges and future directions.

Idiopathic pulmonary fibrosis (IPF) is a progressive disease of unknown aetiology, characterised by a radiological and/or morphological pattern of usu...

Assessing in-hospital mortality risk in ICU lung cancer patients using machine learning: An analysis based on the MIMIC-IV database.

BACKGROUND: Patients with advanced lung cancer admitted to the intensive care unit (ICU) face a substantially elevated risk of in-hospital mortality. ...