Pulmonology

Latest AI and machine learning research in pulmonology for healthcare professionals.

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Evaluation of the mandibular canal and the third mandibular molar relationship by CBCT with a deep learning approach.

OBJECTIVE: The mandibular canal (MC) houses the inferior alveolar nerve. Extraction of the mandibula...

Quantitative fibrosis identifies biliary tract involvement and is associated with outcomes in pediatric autoimmune liver disease.

BACKGROUND: Children with autoimmune liver disease (AILD) may develop fibrosis-related complications...

Past, present, and future of electrical impedance tomography and myography for medical applications: a scoping review.

This scoping review summarizes two emerging electrical impedance technologies: electrical impedance ...

Development and validation of interpretable machine learning models for postoperative pneumonia prediction.

BACKGROUND: Postoperative pneumonia, a prevalent form of hospital-acquired pneumonia, poses signific...

Integrated multi-omics analysis describes immune profiles in ischemic heart failure and identifies PTN as a novel biomarker.

INTRODUCTION: Heart failure is a leading global cause of mortality, with ischemic heart failure (IHF...

Machine learning models for quantitatively prediction of toxicity in macrophages induced by metal oxide nanoparticles.

As nanotechnology advances, metal oxide nanoparticles (MeONPs) increasingly come into contact with h...

DMAMP: A Deep-Learning Model for Detecting Antimicrobial Peptides and Their Multi-Activities.

Due to the broad-spectrum and high-efficiency antibacterial activity, antimicrobial peptides (AMPs) ...

Hyb_SEnc: An Antituberculosis Peptide Predictor Based on a Hybrid Feature Vector and Stacked Ensemble Learning.

Tuberculosis has plagued mankind since ancient times, and the struggle between humans and tuberculos...

Utility of a Large Language Model for Extraction of Clinical Findings from Healthcare Data following Lung Ablation: A Feasibility Study.

To assess the feasibility of utilizing a large language model (LLM) in extracting clinically relevan...

Integrating microbial profiling and machine learning for inference of drowning sites: a forensic investigation in the Northwest River.

Drowning incidents present significant challenges for forensic investigators in determining the exac...

Comparative study of DCNN and image processing based classification of chest X-rays for identification of COVID-19 patients using fine-tuning.

The conventional detection of COVID-19 by evaluating the CT scan images is tiresome, often experienc...

Radiomics-based machine learning for automated detection of Pneumothorax in CT scans.

The increasing complexity of diagnostic imaging often leads to misinterpretations and diagnostic err...

Deep learning using histological images for gene mutation prediction in lung cancer: a multicentre retrospective study.

BACKGROUND: Accurate detection of driver gene mutations is crucial for treatment planning and predic...

Diagnostic modalities in the mediastinum and the role of bronchoscopy in mediastinal assessment: a narrative review.

BACKGROUND AND OBJECTIVE: Diagnosis of pathology in the mediastinum has proven quite challenging, gi...

A machine learning-based risk score for prediction of mechanical ventilation in children with dengue shock syndrome: A retrospective cohort study.

BACKGROUND: Patients with severe dengue who develop severe respiratory failure requiring mechanical ...

Self-supervised learning improves robustness of deep learning lung tumor segmentation models to CT imaging differences.

BACKGROUND: Self-supervised learning (SSL) is an approach to extract useful feature representations ...

Machine learning-aided discovery of T790M-mutant EGFR inhibitor CDDO-Me effectively suppresses non-small cell lung cancer growth.

BACKGROUND: Epidermal growth factor receptor (EGFR) T790M mutation often occurs during long duration...

Machine learning-based prediction of antibiotic resistance in Mycobacterium tuberculosis clinical isolates from Uganda.

BACKGROUND: Efforts toward tuberculosis management and control are challenged by the emergence of My...

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