Pulmonology

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

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An explainable and accurate transformer-based deep learning model for wheeze classification utilizing real-world pediatric data.

Auscultation is a method that involves listening to sounds from the patient's body, mainly using a s...

Deep learning for detecting and early predicting chronic obstructive pulmonary disease from spirogram time series.

Chronic Obstructive Pulmonary Disease (COPD) is a chronic lung condition characterized by airflow ob...

Artificial Intuition and accelerating the process of antimicrobial drug discovery.

New drug development is a very challenging, expensive, and usually time-consuming process. This issu...

Artificial intelligence for individualized treatment of persistent atrial fibrillation: a randomized controlled trial.

Although pulmonary vein isolation (PVI) has become the cornerstone ablation procedure for atrial fib...

Applications of digital health technologies and artificial intelligence algorithms in COPD: systematic review.

BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) represents a significant global health chal...

Artificial intelligence for opportunistic osteoporosis screening with a Hounsfield Unit in chronic obstructive pulmonary disease patients.

INTRODUCTION: To investigate the accuracy of an artificial intelligence (AI) prototype in determinin...

Tailoring ventilation and respiratory management in pediatric critical care: optimizing care with precision medicine.

PURPOSE OF REVIEW: Critically ill children admitted to the intensive care unit frequently need respi...

Liver fibrosis progression analyzed with AI predicts renal decline.

BACKGROUND & AIMS: The relationship between biopsy-proven liver fibrosis progression and renal funct...

The large language model diagnoses tuberculous pleural effusion in pleural effusion patients through clinical feature landscapes.

BACKGROUND: Tuberculous pleural effusion (TPE) is a challenging extrapulmonary manifestation of tube...

Artificial intelligence-assisted point-of-care devices for lung cancer.

Lung cancer is the leading cause of cancer-related deaths worldwide, primarily due to late-stage det...

Deep learning paradigms in lung cancer diagnosis: A methodological review, open challenges, and future directions.

Lung cancer is the leading cause of global cancer-related deaths, which emphasizes the critical impo...

Multi-modality medical image classification with ResoMergeNet for cataract, lung cancer, and breast cancer diagnosis.

The variability in image modalities presents significant challenges in medical image classification,...

Deep Learning Radiomics for Survival Prediction in Non-Small-Cell Lung Cancer Patients from CT Images.

This study aims to apply a multi-modal approach of the deep learning method for survival prediction ...

Supervised Contrastive Learning Framework and Hardware Implementation of Learned ResNet for Real-Time Respiratory Sound Classification.

This paper presents a supervised contrastive learning (SCL) framework for respiratory sound classifi...

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