Pulmonology

Integration of circulating tumor DNA data enhances lung cancer prediction in patients with COPD.

Patients with chronic obstructive pulmonary disease (COPD) are at increased risk of lung cancer, and the identification of circulating tumor DNA (ctDNA) mutations may help detect lung cancer in them. However, whether the addition of ctDNA information improves lung cancer prediction remains to be elucidated. Blood samples from 236 patients with COPD (119 with lung cancer and 117 without lung cancer...

Predicting pyrazinamide resistance in Mycobacterium tuberculosis using a graph convolutional network.

Prediction of high-flow nasal cannula failure in critically ill patients: a narrative review.

High-flow nasal cannula (HFNC) therapy is widely used for respiratory support in critically ill patients, offering benefits such as improved oxygenati...

18F-FDG PET/CT and receptor-positive circulating tumor cells-based machine learning model for predicting poorly differentiated lung adenocarcinoma.

INTRODUCTION: This study aimed to develop and validate a machine learning model that integrates radiomic features from 2-[18F]fluoro-2-deoxy-D-glucose...

Tuberculosis Drug Discovery in the Age of Artificial Intelligence.

There is an urgent need to develop additional treatments for tuberculosis (TB) to complement the small panel of approved drugs and to devise shorter t...

A Deep Learning Framework Integrating Tumor Microenvironmental Features Accurately Predicts Multiple Driver Gene Mutations in Lung Cancer Pathology Images.

UNLABELLED: Deep learning (DL) has the potential to enable the prediction of gene mutations directly from routine histopathology slides in lung cancer...

Distinct Tumor-Immune Ecologies in Patients with Lung Cancer Predict Progression and Define a Clinical Biomarker of Therapy Response.

UNLABELLED: Multiplexed imaging of tissues is an approach that holds promise for improving early detection, diagnosis, and treatment of cancer. In thi...

Deep-learning-based spectral motion artifact correction on photon-counting cardiac CT images.

Objective.While photon-counting computed tomography (PCCT) improves image quality and reduces radiation dose, artifacts induced by cardiac and respira...

MycoPermeNet-v2: Improved Prediction of Mycomembrane Permeation Using Fusion Noisy Student Self-Distillation.

Machine learning (ML) techniques offer a promising path for accelerating antibiotic discovery by computationally predicting and optimizing desirable p...

ARIMA-based forecasting of cerebral physiologic signals in acute traumatic brain injury: a CAnadian high-resolution TBI (CAHR-TBI) cohort study.

BACKGROUND: Traumatic brain injury (TBI) remains a major global health issue, with limited progress in reducing morbidity and mortality for TBI patien...

Facile Critical Evaluation of Extensive Lithium-Oxygen Battery Literature Using In-House Data and the Structured Query Learning-Retrieval-Augmented Generation Method.

Lithium-oxygen batteries (LOBs) offer combustion fuel-like energy densities but remain constrained by low efficiency, limited cycle life, and coupled ...

PSA-1DCNN: Multimodal Biomarker and Text Integration for Lung Cancer Diagnosis.

Integrating multimodal data, such as unstructured clinical narratives and quantitative blood biomarkers, remains a major challenge in modern healthcar...

Multimodal AI-based 28-day mortality prediction of pneumonia patients at ED discharge: a multicenter study.

Interpretable machine learning model for predicting the risk of dysphagia in patients after cardiac surgery.

BACKGROUND: Dysphagia is recognized as one of the most common severe complications following cardiac surgery, with the potential to result in adverse ...

Feasibility of Implicit Neural Representation Learned Motion Compensation for 3D Stack-of-Spirals Free-Breathing Cardiac Quantitative Susceptibility Mapping.

PURPOSE: Differential blood oxygenation between the right and left heart (ΔSO2) is an indicator of cardiovascular function currently assessed in clini...

Developing a Metabolic-Associated Prognostic Index for Risk Stratification and Therapeutic Guidance in Stage I Lung Adenocarcinoma via Multiomics Analysis.

PURPOSE: Early-stage lung adenocarcinoma (LUAD) exhibits substantial clinical heterogeneity that is not fully explained by TNM staging, highlighting t...

Sustainable Strategies in Tuberculosis Management: Bridging Ethnobotanical Pharmacology, Advanced Drug Delivery, and AI-Driven Innovation.

Tuberculosis (TB) persists as a leading infectious disease, with progress in global control complicated by emerging drug resistance, limited access to...

Emerging Trends and Innovations in Radiologic Diagnosis of Thoracic Diseases.

Over the past decade, Investigative Radiology has published numerous studies that have fundamentally advanced the field of thoracic imaging. This revi...

Lung-DDPM: Semantic Layout-Guided Diffusion Models for Thoracic CT Image Synthesis.

With the rapid development of artificial intelligence (AI), AI-assisted medical imaging analysis demonstrates remarkable performance in early lung can...

Quantitative Chest Computed Tomography and Machine Learning for Subphenotyping Small Airways Disease in Long COVID.

PURPOSE: To investigate imaging phenotypes in posthospitalized COVID-19 patients by integrating quantitative CT (QCT) and machine learning (ML), with ...