Pulmonology

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

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Mechanical Ventilation Guided by Electrical Impedance Tomography in Children With Acute Lung Injury.

OBJECTIVES: To provide proof-of-concept for a protocol applying a strategy of personalized mechanica...

Lung Cancer Detection using Probabilistic Neural Network with modified Crow-Search Algorithm.

Objective: Lung cancer is a type of malignancy that occurs most commonly among men and the third mos...

Machine learning-based radiomics strategy for prediction of cell proliferation in non-small cell lung cancer.

PURPOSE: To explore the feasibility and performance of machine learning-based radiomics classifier t...

Respiratory Sound Based Classification of Chronic Obstructive Pulmonary Disease: a Risk Stratification Approach in Machine Learning Paradigm.

This article investigates the classification of normal and COPD subjects on the basis of respiratory...

Using machine learning to examine the relationship between asthma and absenteeism.

In this study, we found that machine learning was able to effectively estimate student learning outc...

An image-based deep learning framework for individualizing radiotherapy dose.

BACKGROUND: Radiotherapy continues to be delivered uniformly without consideration of individual tum...

Automatic Multi-Level In-Exhale Segmentation and Enhanced Generalized S-Transform for wheezing detection.

BACKGROUND AND OBJECTIVE: Wheezing is a common symptom of patients caused by asthma and chronic obst...

Object Detection During Newborn Resuscitation Activities.

OBJECTIVE: Birth asphyxia is a major newborn mortality problem in low-resource countries. Internatio...

Feasibility of Natural Language Processing-Assisted Auditing of Critical Findings in Chest Radiology.

OBJECTIVE: Time-sensitive communication of critical imaging findings like pneumothorax or pulmonary ...

Automated detection of third molars and mandibular nerve by deep learning.

The approximity of the inferior alveolar nerve (IAN) to the roots of lower third molars (M3) is a ri...

Classification of benign and malignant lung nodules from CT images based on hybrid features.

The classification of benign and malignant lung nodules has great significance for the early detecti...

Diagnostic value of spirometry vs impulse oscillometry: A comparative study in children with sickle cell disease.

BACKGROUND: Spirometry is conventionally used to diagnose airway diseases in children with sickle ce...

Deep Learning-based Image Conversion of CT Reconstruction Kernels Improves Radiomics Reproducibility for Pulmonary Nodules or Masses.

Background Intratumor heterogeneity in lung cancer may influence outcomes. CT radiomics seeks to ass...

Conservation region finding for influenza A viruses by machine learning methods of N-linked glycosylation sites and B-cell epitopes.

Influenza type A, a serious infectious disease of the human respiratory tract, poses an enormous thr...

Three-dimensional dose prediction for lung IMRT patients with deep neural networks: robust learning from heterogeneous beam configurations.

PURPOSE: The use of neural networks to directly predict three-dimensional dose distributions for aut...

Artificial intelligence and radiomics in pulmonary nodule management: current status and future applications.

Artificial intelligence (AI) has been present in some guise within the field of radiology for over 5...

Fusing learned representations from Riesz Filters and Deep CNN for lung tissue classification.

A novel method to detect and classify several classes of diseased and healthy lung tissue in CT (Com...

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