Pulmonology

Integrated in silico and in vitro screening approaches for the discovery of small-molecule inhibitors of β-carbonic anhydrases.

INTRODUCTION: β-Carbonic anhydrases (β-CAs) are zinc-dependent metalloenzymes that catalyze the reversible hydration of carbon dioxide to bicarbonate and protons. They are widely distributed in bacteria, where they support pH regulation, inorganic carbon homeostasis, and central metabolism. Unlike humans, which express only α-class carbonic anhydrases, many bacterial pathogens encode β-CAs, highli...

Defining Physician-AI Collaboration in Pulmonary and Critical Care Medicine: Concepts and Illustrative Examples for Clinical Reasoning.

The exponential growth of medical data and complexity in Pulmonary and Critical Care Medicine (PCCM) necessitates a paradigm shift in clinical reasoning and education. This paper proposes a structured framework for collaborative decision-making between physicians and artificial intelligence (AI) that emphasizes the integration of critical thinking with AI-enhanced capabilities. Critical thinking i...

Research on Lung Cancer Classification Based on Multidimensional Hematological Indicators and Machine Learning Models.

Accurate subtyping of lung cancer is crucial for developing personalized treatment plans and improving patient outcomes. This study established machin...

Prediction of Postoperative Pancreatic Fistula Occurrence by the Pancreatic Stump Shape and Remnant Pancreatic Volume Measured Using AI-Guided Three-Dimensional Simulation.

BACKGROUND: When three-dimensional computer graphics (3DCG) images are used, artificial intelligence (AI) engines can semiautomatically estimate the p...

Moving Beyond Morphology: Toward a Morpho-Molecular Classification of Pleural Mesothelioma.

Despite recent advances in the treatment of pleural mesothelioma, it remains a challenging and heterogeneous disease, with limited options for patient...

KD-SqueezeNet: an efficient deep learning strategy for the multi-task diagnosis of neonatal lung diseases.

BACKGROUND: The integration of deep learning in medical imaging has reached proficiency levels akin to expert clinicians, particularly in tasks requir...

Multidimensional analysis of postoperative nursing challenges in oral cancer surgery: a retrospective study of 245 patients and proposal of the PROTECT mode.

PURPOSE: The quality of postoperative care for oral tumors critically influences patient prognosis and quality of life; however, current nursing syste...

Translating Mechanistic Insights Into Action and Revealing New Pathways: Machine Learning Approaches in Heart Failure With Preserved Ejection Fraction.

Heart failure with preserved ejection fraction is a prevalent condition that carries a high morbidity and mortality, with limited treatment options. O...

Multimodal ultrasound and artificial intelligence for characterization of thyroid nodules in Hashimoto's thyroiditis: current challenges and future perspectives.

Patients with Hashimoto's thyroiditis (HT) frequently present with concurrent nodular lesions such as nodular goiter and thyroid cancer (especially pa...

Topologically distinct 2D and 3D intratumoral heterogeneity scores for preoperatively predicting invasiveness in stage I lung adenocarcinoma: A multicenter study.

This multicenter study aims to enhance the preoperative prediction of pathological invasiveness in clinical stage I lung adenocarcinoma (LUAD) by deve...

Prediction of COVID-19 hospitalisation, ICU admission or death following ChAdOx1 vaccination using artificial intelligence: A clinical predictive model from the English RAVEN study.

OBJECTIVES: This study identifies predictors of severe COVID-19 following completion of two-dose primary series of the AZD1222 COVID-19 vaccine, emplo...

A hybrid CNN-spectral architecture for non-contact respiratory rate estimation using multi-region optical-flow analysis.

Respiratory rate (RR) is a key indicator for assessing health conditions, yet noncontact measurement remains challenging due to motion artifacts, ligh...

Generation of machine-learning derived cancer vulnerability indicator to determine the spatial burden of cancer outcomes.

BACKGROUND: Due to the difficulty of obtaining population-based individual-level data, ecological studies are often used to explore factors related to...

Aortic and Cardiac Structure From Routine CT Predict Cardiovascular Risk Beyond PREVENT and Coronary Calcium.

BACKGROUND: Cardiovascular disease prevention relies on accurate risk assessment; however, existing scores are imprecise. Routine imaging may be oppor...

The impact of chest computed tomography-defined emphysema on extrapulmonary metastases in patients with lung cancer.

Fusing data from CT deep learning, CT radiomics and peripheral blood immune profiles to diagnose lung cancer in a cohort of patients experiencing symptoms.

BACKGROUND: Lung cancer is the leading cause of cancer-related deaths. Diagnosis at late stages is common due to the largely non-specific nature of pr...

Histopathological diagnosis of Ovine Pulmonary Adenocarcinoma (OPA) based on ensemble model.

Automated Detection of Ventilator Asynchronies: A Clinical and Technological Perspective.

Patient-ventilator asynchrony is highly prevalent during invasive mechanical ventilation, yet its detection at the bedside remains limited. Convention...

Clinical History, Spirometry, and CT Features Can Predict Dyspnea in Smokers with and without Spirometry-Defined COPD.

ASO Visual Abstract: CT-Based Prediction of Visceral Pleural Invasion in Lung Adenocarcinoma ≤ 3 cm: Enhancing Deep Learning Specificity by Waiving Chest Wall Information.