Pulmonology

Explainable multimodal deep learning models for variable-length sequences in critically ill patients.

OBJECTIVE: Deep learning models have shown strong performance in predicting clinical events in critical care using structured electronic health record (EHR) data. While incorporating unstructured notes improves accuracy, multimodal fusion and explainability remain an open challenge, particularly for variable-length temporal data. This study develops an explainable temporal modeling framework for m...

Salvianolic acid C attenuates liver fibrosis and inhibites hepatic stellate cell activation by targeting FAP/TβRI/SMAD axis.

BACKGROUND: Liver fibrosis remains a major clinical challenge with limited effective therapeutic options. Salvianolic acid C (SAC), a major water-soluble compound derived from Salvia miltiorrhiza, has shown anti-fibrotic activity in various disease models; however, its role and underlying mechanisms in liver fibrosis remain unclear. METHODS: A CCl4-induced mouse model was used to assess the in viv...

LUMI-lab: A foundation model-driven autonomous platform enabling discovery of ionizable lipid designs for mRNA delivery.

Integrating AI with robotics offers a promising approach to molecular discovery and optimization, enabling efficient exploration of vast chemical spac...

Real-Time MRI With Deep Learning for Efficient Evaluation of Neuromuscular Breathing Impairment.

Efficient detection of breathing impairment is critical for treatment and prognosis in neuromuscular disorders. However, standard pulmonary function t...

Transcriptome Profiling of Peripheral Blood for Inflammatory Subtype Classification and Diagnostic Model Construction in Asthma.

OBJECTIVE: This study aimed to identify inflammatory subtypes of asthma using peripheral blood transcriptomics and to derive candidate biomarkers supp...

From guidelines to algorithms: the future of AI-augmented asthma care.

PURPOSE OF REVIEW: Artificial intelligence (AI) has emerged as an increasingly accessible and influential resource within both public and clinical dom...

Non-pharmacological treatment of AECOPD.

Acute exacerbations of chronic obstructive pulmonary disease (AECOPDs) are acute events characterized by rapid worsening of dyspnea, cough, and sputum...

Longitudinal multisource clinical model for early lung cancer risk stratification and screening.

OBJECTIVES: Lung cancer is the leading cause of cancer-related mortality worldwide, with poor prognosis largely due to late-stage diagnosis. Current s...

Predicting low oxygen in patients with acute COVID-19 infection isolating at home: a clinical prediction model.

RATIONALE: Identifying patients who could be safely managed at home versus those needing hospitalisation was a particular concern during early COVID-1...

Robust learning framework for a scalable remote monitoring of autonomic dysreflexia: use-case in spinal cord injury.

The autonomous nervous system (ANS) response in neurological disorders is a direct modifiable risk factor for cardiovascular health, however, difficul...

Natriuretic peptides and cardiac troponins in hypertension and heart failure: A contemporary review of the evidence.

Hypertension is the second leading cause of heart failure (HF), yet strategies for identifying hypertensive individuals at increased HF risk remain li...

Deep learning models for pulmonary embolism segmentation on dual-energy CT: performance analysis and image quality correlation.

Artificial intelligence-based image recognition in bronchoscopy: software development and randomized controlled trial for training evaluation in intensive care residents.

Acute respiratory infections prediction through social media data and machine learning: a systematic review.

The rise of artificial intelligence in respiratory primary care and pulmonology: a scoping review.

Artificial intelligence (AI) is rapidly advancing respiratory disease management, from diagnosis to population lung health. This scoping review synthe...

Utility of breath-hold half-Fourier single-shot turbo spin-echo with deep learning-based reconstruction for acquiring fat-suppressed T2-weighted images of the pancreas.

PURPOSE: To determine the best technique for acquiring fat-suppressed T2-weighted images (FS-T2WI) of the pancreas, in terms of acquisition time and i...

A Deep Learning Model for Artery of Adamkiewicz Detection in Bronchial Artery Embolization: A Multicenter Retrospective Study.

PURPOSE: To evaluate the effectiveness of a deep learning model for recognizing the artery of Adamkiewicz and anterior spinal artery (ASA) to prevent ...

ALDH1L2 induces resistance to chemotherapy in small cell lung cancer by inhibiting ferroptosis.

Small cell lung cancer (SCLC) is known for its rapid growth and early metastasis, and SCLC patients are highly susceptible to chemoresistance. Studies...

Subclassification of Small Cell Lung Cancer Based on Gene Expression Signatures and Machine Learning.

Small-cell lung cancer (SCLC) is frequently subdivided into four molecular subtypes according to the activity of key transcription factors (TFs) NEURO...

From muscle to motion: GaIn nanoparticle-TPU core/shell mesh electrodes for intelligent prosthesis.

Electromyography (EMG) electrodes are critical for detecting and interpreting muscle activity, which is essential for operating prosthetic devices and...