Pulmonology

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

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Stress Classification and Vital Signs Forecasting for IoT-Health Monitoring.

Health monitoring embedded with intelligence is the demand of the day. In this era of a large popula...

A Deep Learning Approach Considering Image Background for Pneumonia Identification Using Explainable AI (XAI).

Pneumonia mainly refers to lung infections caused by pathogens, such as bacteria and viruses. Curren...

AI-based automation of enrollment criteria and endpoint assessment in clinical trials in liver diseases.

Clinical trials in metabolic dysfunction-associated steatohepatitis (MASH, formerly known as nonalco...

An integrated deep learning approach for modeling dissolved oxygen concentration at coastal inlets based on hydro-climatic parameters.

Climate change has a significant impact on dissolved oxygen (DO) concentrations, particularly in coa...

Deep learning ensemble approach with explainable AI for lung and colon cancer classification using advanced hyperparameter tuning.

Lung and colon cancers are leading contributors to cancer-related fatalities globally, distinguished...

Machine learning prediction of pulmonary oxygen uptake from muscle oxygen in cycling.

The purpose of this study was to test whether a machine learning model can accurately predict VO acr...

MPCNN: A Novel Matrix Profile Approach for CNN-based Single Lead Sleep Apnea in Classification Problem.

Sleep apnea (SA) is a significant respiratory condition that poses a major global health challenge. ...

Integrating knowledge graphs into machine learning models for survival prediction and biomarker discovery in patients with non-small-cell lung cancer.

Accurate survival prediction for Non-Small Cell Lung Cancer (NSCLC) patients remains a significant c...

Quantitative drug susceptibility testing for Mycobacterium tuberculosis using unassembled sequencing data and machine learning.

There remains a clinical need for better approaches to rapid drug susceptibility testing in view of ...

Machine learning investigation of tuberculosis with medicine immunity impact.

Tuberculosis (T.B.) remains a prominent global cause of health challenges and death, exacerbated by ...

Optimizing BenMAP health impact assessment with meteorological factor driven machine learning models.

This study aims to address accuracy challenges in assessing air pollution health impacts using Envir...

Performance of AI for preoperative CT assessment of lung metastases: Retrospective analysis of 167 patients.

OBJECTIVES: To evaluate the performance of artificial intelligence (AI) in the preoperative detectio...

Effect of Deep Learning Image Reconstruction Algorithms on Radiomic Features of Pulmonary Nodules in Ultra-Low-Dose CT.

OBJECTIVE: The purpose of this study is to explore the impact of deep learning image reconstruction ...

Structure and position-aware graph neural network for airway labeling.

We present a novel graph-based approach for labeling the anatomical branches of a given airway tree ...

Clinical implementation and evaluation of deep learning-assisted automatic radiotherapy treatment planning for lung cancer.

PURPOSE: The purpose of the study is to investigate the clinical application of deep learning (DL)-a...

Interpretation of acid-base metabolism on arterial blood gas samples via machine learning algorithms.

BACKGROUND: Arterial blood gas evaluation is crucial for critically ill patients, as it provides ess...

Early predictive values of clinical assessments for ARDS mortality: a machine-learning approach.

Acute respiratory distress syndrome (ARDS) is a devastating critical care syndrome with significant ...

Evaluating the accuracy of lung-RADS score extraction from radiology reports: Manual entry versus natural language processing.

INTRODUCTION: Radiology scoring systems are critical to the success of lung cancer screening (LCS) p...

Single-center outcomes of artificial intelligence in management of pulmonary embolism and pulmonary embolism response team activation.

Multidisciplinary pulmonary embolism response teams (PERTs) have shown that timely triage expedites ...

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