Pulmonology

Response to the Letter "Comment on Analysis of Models to Estimate Morbidity Rates of Respiratory Diseases Through Deep Learning".

Comment on 'Analysis of Models to Estimate Morbidity Rates of Respiratory Diseases Through Deep Learning'.

Machine Learning Analysis of Single-Cell Transcriptomics Identifies a B-Cell-Associated Fibroblast Signature Predictive of Renal Fibrosis Severity.

BACKGROUND: Renal fibrosis represents the final common pathway of chronic kidney disease (CKD); however, both its definitive diagnostic biomarkers and...

CDKN3, PKP2, ADM, MS4A1, FAM83A, and DKK1 Define a Posttranslational Modification (PTM)-Associated Prognostic Model for Lung Adenocarcinoma.

INTRODUCTION: Posttranslational modification (PTM) plays an important role in protein regulation and may influence tumor initiation and progression. H...

AI for tumour proportion scoring of programmed death-ligand 1 immunohistochemistry in non-small cell lung cancer: a review of commercial and non-commercial tools.

Programmed death-ligand 1 (PD-L1) expression, commonly quantified as tumour proportion score (TPS), is a key biomarker guiding immunotherapy in non-sm...

Development and Internal Evaluation of a Deep Learning Model for Fine-Grained Detection of Dental Trauma on CBCT-Dominant Image Records.

OBJECTIVES: To develop and internally evaluate a YOLO-based model for fine-grained localization and classification of dental trauma subtypes. METHODS:...

Corticosteroid Stewardship: Can it help us avoid the corticosteroid trap? Journal of Allergy and Clinical Immunology: In Practice.

With an almost 20-year experience with asthma biologics, it is now clear that a major impact of all available asthma biologics is the opportunity to r...

Autonomous Vascular Access Devices: Current Solutions and Future Challenges.

INTRODUCTION: Central venous cannulation is essential for life-saving interventions including resuscitation of critically ill patients, hemodynamic mo...

Identification of Mitotic Catastrophe-related Prognostic Genes in Lung Adenocarcinoma via Transcriptome Analysis.

Lung adenocarcinoma (LUAD), the most common lung cancer subtype, exhibits a poor prognosis. Although mitotic catastrophe can be induced in LUAD, leadi...

EXPRESS: Relation between Albumin-Corrected Anion Gap and In-Hospital Mortality in Patients with Traumatic Lung Injury: A Multicenter Retrospective Cohort Study and the Development of Machine Learning-Based Prediction Models.

BACKGROUND: The anion gap is primarily utilized as an indicator for evaluating acid-base imbalances in critically ill patients. However, its accuracy ...

Evaluation of Differential Diagnosis of Odontogenic Lesions in Cone Beam Computed Tomography Images Using Radiomics-Based Machine Learning.

OBJECTIVE: This study aimed to evaluate the structural characteristics of mandibular alveolar bone in patients with Type 1 diabetes mellitus (T1DM), T...

Perception and accuracy of an AI-based contactless wellness screening system in dental setting; a cross-sectional study.

This study evaluates the reliability and participants' responses to a contactless artificial intelligence (AI) device powered by Remote Photoplethysmo...

Risk Factors for Pediatric Acute Chest Syndrome Utilizing Machine Learning Techniques.

Acute chest syndrome (ACS) causes significant morbidity and mortality in both adult and pediatric patients with sickle cell disease (SCD). Despite kno...

Artificial count enhancement in lung scintigraphy for acquisition acceleration and pseudo-planar generation.

Ventilation-perfusion (V/Q) planar scintigraphy remains widely used for diagnosing pulmonary embolism (PE), despite the reported superior diagnos...

Development and Independent Validation of a Machine Learning-Based Non-Invasive Venous Waveform Analysis for Heart Failure (NIVAHF) Device to Estimate Pulmonary Capillary Wedge Pressure.

BACKGROUND: Hemodynamic-guided management improves outcomes in heart failure (HF), but implantable pulmonary artery pressure monitoring is limited by ...

Artificial Intelligence-Assisted Chest Radiography: A Prospective Crossover Multi-Reader Study on Diagnostic Performance and Workflow Efficiency.

RATIONALE AND OBJECTIVES: To evaluate the impact of four commercially available AI solutions for chest radiography on diagnostic performance, workflow...

Composite dietary antioxidant index with hepatic indices for predicting mortality in cardiovascular-kidney-metabolic syndrome: Integrated analysis of a nationwide cohort study using machine learning approaches.

Oxidative stress is a pathological driver of cardiovascular-kidney-metabolic (CKM) syndrome, exacerbating inflammation and tissue injury, while metabo...

The association between serum chloride levels and asthma prevalence: A cross-sectional study with variable screening and validation guided by machine learning.

Prior evidence suggests that ion channel dysfunction plays a significant role in the pathogenesis of asthma, which provides a theoretical basis for th...

Radiological assessment of pulmonary vascularity in congenital heart disease: standardized clinician assessment versus deep learning-based prediction.

BACKGROUND: Assessment of pulmonary vascularity on chest radiographs (CXRs) in congenital heart disease (CHD) is limited by subjectivity, and existing...

Single-photon emission computed tomography/computed tomography-based radiomics of bone metastases for predicting epidermal growth factor receptor mutation status and targeted therapy efficacy in non-small-cell lung cancer.

BACKGROUND: This study aimed to develop a single-photon emission computed tomography/computed tomography (SPECT/CT)-based radiomics model using bone m...