Pulmonology

Clinical evaluation of an AI-based pneumonia detection system on chest CT: a qualitative and quantitative analysis.

Artificial intelligence (AI) for early identification of radiotherapy related toxicities from the electronic health records of patients with head and neck cancer.

We evaluated artificial intelligence (AI) for detecting osteoradionecrosis, fibrosis, trismus, and dysphagia in 207 head and neck cancer patient electronic health records. After adjudication and fine-tuning, accuracy reached 87% (F1 = 0.92). The model processed 20,835 sentences within seconds, demonstrating feasibility and efficiency for automating the identification of radiation-related late toxi...

Raman analysis of black carbon using artificial neural networks for emission source classification.

Black Carbon (BC), a major component of Particulate Matter (PM), plays a crucial role in air pollution, climate change, and public health impacts, due...

Artificial intelligence-enhanced three-dimensional radiological analysis for predicting spread through air spaces in early-stage lung adenocarcinoma.

OBJECTIVES: Spread through air space (STAS) is a pathological feature that correlates with poor prognosis, especially in patients with lung adenocarci...

Ischaemia in tuberculous meningitis: update on pathophysiology, clinical predictors and management.

PURPOSE OF REVIEW: Tuberculous meningitis (TBM) is a severe manifestation of Mycobacterium tuberculosis infection, associated with high mortality and ...

Targeting immunosenescence in lung diseases: mechanistic insights and clinical interventions.

Immunosenescence, the age-related decline in immune function, plays a crucial role in the pathogenesis and progression of lung diseases, including chr...

Opportunistic Screening on Chest CT, From the AJR Special Series on Screening.

The increase in chest CT volumes affords radiologists the opportunity to systematically assess imaging biomarkers, including coronary and thoracic art...

Healthcare-associated infections in Italian long-term care facilities: a machine learning analysis of a 12-month cohort.

OBJECTIVES: To estimate the incidence of healthcare-associated infections (HAIs) in Italian long-term care facilities (LTCFs) and to evaluate whether ...

Does Hypotension Prediction Index limit the occurrence of postoperative complications associated with intraoperative hypotension? A systematic review and model-averaged Bayesian meta-analysis of statistically sound studies.

Intraoperative hypotension (IOH) is considered a potential contributing factor to postoperative complications. In 2018, a machine-learning algorithm t...

Plasma proteomic signatures linking preserved ratio impaired spirometry to cardiometabolic diseases and multimorbidity: A longitudinal cohort study.

BACKGROUND: Preserved ratio impaired spirometry (PRISm), defined by reduced FEV1 with preserved FEV1/FVC ratio, has been linked to cardiometabolic dis...

A unified multimodal framework for chest X-ray retrieval and disease prediction for clinical decision support.

Recent advances in medical imaging and natural language processing enable new opportunities for automated diagnostic support. Chest X-rays (CXRs) rema...

Antimicrobial peptides in malaria and tuberculosis management: a systematic review of emerging evidence.

AMPs (Antimicrobial peptides) are small molecules that are crucial components of biological activities, viz wound healing, angiogenesis, antimicrobial...

Automated contrast-to-noise ratio analysis in chest CT: validation of an open-source segmentation approach.

OBJECTIVES: This study aimed to evaluate the feasibility and accuracy of automated contrast-to-noise ratio (CNR) analysis in chest CT using the open-s...

Research on lung nodule detection in X-ray plain films based on improved YOLOv12 model.

To improve automatic lung nodule detection in chest X-ray images, this study proposes an improved YOLOv12-based detection framework by integrating spa...

Development and validation of a clinical nomogram for frailty prediction in older COPD patients: a machine learning approach.

A multimodal predictive model incorporating transcriptomic-guided blood biomarkers and clinical variables for sepsis-associated acute kidney injury.

Sepsis-associated acute kidney injury (SA-AKI) is a major complication in the intensive care unit (ICU), and early risk stratification remains challen...

Dual biomarkers ALOX5AP and INPP4A are associated with lipid metabolism and neutrophil extracellular traps in periodontitis: A bioinformatics and clinical validation study.

OBJECTIVE(S): Periodontitis is a chronic inflammatory disease characterized by progressive alveolar bone destruction. While lipid metabolism and neutr...

Survival prediction in non-small cell lung cancer using layer-wise radiomics and stacked radscore integration: a multi-institutional study.

OBJECTIVES: To enhance prognostic modeling in patients with non-small cell lung cancer (NSCLC), we developed and externally validated a novel radiomic...

Three decades of hemodynamic monitoring (1995-2025): from invasive pressure based hemodynamic profiling to functional physiology.

PURPOSE OF REVIEW: Hemodynamic monitoring has undergone a profound transformation over the last 30 years. The field has transitioned from the "standar...

Artificial intelligence-based detection of acute postoperative airway complications following anterior cervical spine surgery: a retrospective imaging evaluation.

STUDY DESIGN: Retrospective imaging evaluation using an artificial intelligence (AI)-generated model. PURPOSE: To develop novel AI software for early ...