Pulmonology

AI-assisted chest radiograph interpretation enhances diagnostic confidence and standardizes diagnostic accuracy across radiologists: A multi-reader study.

PURPOSE: To evaluate the impact of an artificial intelligence (AI)-assisted computer-aided detection (CAD) system on the diagnostic accuracy and confidence in chest radiograph interpretation among nonthoracic radiologists and radiology residents with varying levels of experience. METHODS: In this retrospective multiple-reader, multiple-case (MRMC) study, 400 chest radiographs (100 each for pulmona...

INTELLI-PVA: Informative sample annotation-based contrastive active learning for cross-domain patient-ventilator asynchrony detection.

BACKGROUND AND OBJECTIVE: Patient-ventilator asynchrony (PVA) is prevalent in mechanically ventilated patients and adversely impacts clinical outcomes, but its real-time detection remains challenging. While artificial intelligence (AI) systems show promise for PVA detection, their cross-domain generalization faces two major limitations: variability in patient-ventilator interactions across differe...

Design of the first national lung cancer screening program in the European Union: the Croatian Model.

OBJECTIVES: To address Croatia's high lung cancer mortality and late-stage diagnoses, the Ministry of Health initiated a multidisciplinary effort to d...

A novel hybrid sensor array with enhanced sensitivity and selectivity for biomarker detection of multiple respiratory diseases.

Electronic nose is an emergent technique for noninvasive disease detection via breath analysis, which is, however limited by the sensitivity and selec...

Accurate single-domain scaffolding of three nonoverlapping protein epitopes using deep learning.

De novo protein design has seen major success in scaffolding single functional motifs; however, in nature, most proteins present multiple functional s...

Developing and Validating a Prediction Model for the Severe Pain-Fatigue-Sleep Disturbance Symptom Cluster in Patients with Lung Cancer Following Chemotherapy: A Machine Learning Analysis.

OBJECTIVES: Pain-fatigue-sleep disturbance symptom (PFS) cluster is the most common symptom cluster in patients with lung cancer following chemotherap...

Environmental exposures, epithelial barrier dysfunction, and the evolving landscape of allergic disorders and asthma.

PURPOSE OF REVIEW: Immediate hypersensitivity disorders, such as asthma, food intolerance, and anaphylaxis, have risen dramatically since the 20th cen...

Machine learning models for predicting response to epidermal growth factor receptor tyrosine kinase inhibitors in non-small cell lung cancer brain metastases: a systematic review and meta-analysis.

BACKGROUND: Predicting clinical and radiological outcomes of epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) in patients with ...

Trajectories in renal perfusion pressure during hemodynamically guided therapy are associated with worsening renal function and patient outcomes.

BACKGROUND: Worsening renal function (WRF) during acute decompensated heart failure (ADHF) therapy portends worse outcomes. We hypothesized that renal...

Machine Learning for Classification in Lung Cancer Using Routine Clinical and Laboratory Data.

BACKGROUND: Accurate pathological classification of lung cancer is essential for informing treatment strategies. However, invasive biopsy procedures a...

Development of advanced lung cancer inflammation index-based machine learning models for predicting stroke and mortality: A comparative and interpretable study.

BACKGROUND: The Advanced Lung Cancer Inflammation Index (ALI) is a novel composite index that enables a more holistic evaluation of inflammation and n...

Machine Learning-Augmented Graphene Transistor Biosensing: Quantitative Platform Validation and Immunotesting of Hepatitis E.

Graphene-based chips face persistent sensor-to-sensor variability due to manufacturing defects and polymer contamination, limiting their analytical re...

3D Automated Segmentation of Bronchial Abnormalities on Ultrashort Echo Time MRI: A Quantitative MR Outcome in Cystic Fibrosis.

BACKGROUND: Cystic fibrosis (CF) monitoring relies on computed tomography (CT), but ultra-short echo time MRI (UTE-MRI) offers a radiation-free altern...

Development of a machine learning model for preoperative prediction of spread through air spaces in resectable non-small cell lung cancer: A single-center retrospective study.

Spread through air spaces (STAS) is a pathological feature associated with poor prognosis in non-small cell lung cancer (NSCLC). However, its diagnosi...

Wildfire-sourced PM2.5 and cause-specific emergency department visits in Victoria, Australia from 2014 to 2019.

Wildfires-sourced (WS) fine particulate matter (PM2.5) is known to adversely impact human health, while evidence regarding the burden of emergency dep...

Prediction of respiratory rate from schlieren images using artificial intelligence.

BACKGROUND AND OBJECTIVE: Respiratory rate is a fundamental physiological parameter and one of the earliest indicators that plays a crucial role in as...

Automated quality assurance of imaging dose and protocol adherence in computed tomography radiotherapy planning using TotalSegmentator-based segmentation.

PURPOSE: Computed tomography (CT) scans are vital for radiotherapy planning, providing essential data for dose calculations. This study retrospectivel...

An Explainable Deep Model for Risk Scoring and Accurate Radionecrosis Identification Following Brain Metastasis Stereotactic Radiosurgery.

PURPOSE: As survival improves for patients with brain metastases (BM), distinguishing local recurrence (LR) from radionecrosis (RN) is a growing neuro...

Pressure injury surveillance in the intensive care unit: Development, validation, and clinical application of a natural language processing algorithm.

INTRODUCTION: Pressure injuries (PIs) are one of the most common hospital-acquired complications in patients admitted to an intensive care unit (ICU)....

Prediction of Lung Metastasis in Breast Cancer Patients Using Machine Learning Classifiers.

Breast cancer is the most common cancer among women, and metastasis to the lung is associated with poor prognosis. Reliable biomarkers for predicting ...