Pulmonology

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

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Deep learning for predicting the risk of immune checkpoint inhibitor-related pneumonitis in lung cancer.

AIM: To develop and validate a nomogram model that combines computed tomography (CT)-based radiologi...

Sybil: A Validated Deep Learning Model to Predict Future Lung Cancer Risk From a Single Low-Dose Chest Computed Tomography.

PURPOSE: Low-dose computed tomography (LDCT) for lung cancer screening is effective, although most e...

Current Advances in Computational Lung Ultrasound Imaging: A Review.

In the field of biomedical imaging, ultrasonography has become common practice, and used as an impor...

Coronavirus covid-19 detection by means of explainable deep learning.

The coronavirus is caused by the infection of the SARS-CoV-2 virus: it represents a complex and new ...

Robot-assisted complex urinary tract reconstruction using intestinal segments: redefining the paradigm.

Complex urinary tract reconstruction has significantly advanced with the increasing use of robot-ass...

Predicting N2 lymph node metastasis in presurgical stage I-II non-small cell lung cancer using multiview radiomics and deep learning method.

BACKGROUND: Accurate diagnosis of N2 lymph node status of the resectable stage I-II non-small cell l...

Hospital crowdedness evaluation and in-hospital resource allocation based on image recognition technology.

How to allocate the existing medical resources reasonably, alleviate hospital congestion and improve...

Compensation for respiratory motion-induced signal loss and phase corruption in free-breathing self-navigated cine DENSE using deep learning.

PURPOSE: To introduce a model that describes the effects of rigid translation due to respiratory mot...

Haemodynamic and respiratory perioperative outcomes for open versus robot-assisted radical cystectomy: A double-blinded, randomised trial.

BACKGROUND: The clinical impact of prolonged steep Trendelenburg position and CO pneumoperitoneum du...

Lung Sound Recognition Method Based on Wavelet Feature Enhancement and Time-Frequency Synchronous Modeling.

Lung diseases are serious threats to human health and life, therefore, an accurate diagnosis of lung...

Development and Validation of a Deep Learning-Based Synthetic Bone-Suppressed Model for Pulmonary Nodule Detection in Chest Radiographs.

IMPORTANCE: Dual-energy chest radiography exhibits better sensitivity than single-energy chest radio...

LDDNet: A Deep Learning Framework for the Diagnosis of Infectious Lung Diseases.

This paper proposes a new deep learning (DL) framework for the analysis of lung diseases, including ...

Raman microspectroscopy and machine learning for use in identifying radiation-induced lung toxicity.

OBJECTIVE: In this work, we explore and develop a method that uses Raman spectroscopy to measure and...

Prognostic significance of pulmonary arterial wedge pressure estimated by deep learning in acute heart failure.

AIMS: Acute decompensated heart failure (ADHF) presents with pulmonary congestion, which is caused b...

TNN: Tree Neural Network for Airway Anatomical Labeling.

Detailed anatomical labeling of bronchial trees extracted from CT images can be used as fine-grained...

Feasibility study of deep learning-based markerless real-time lung tumor tracking with orthogonal X-ray projection images.

PURPOSE: The feasibility of a deep learning-based markerless real-time tumor tracking (RTTT) method ...

Painless and accurate medical image analysis using deep reinforcement learning with task-oriented homogenized automatic pre-processing.

Pre-processing is widely applied in medical image analysis to remove the interference information. H...

An accurate deep learning model for wheezing in children using real world data.

Auscultation is an important diagnostic method for lung diseases. However, it is a subjective modali...

Machine learning-based techniques to improve lung transplantation outcomes and complications: a systematic review.

BACKGROUND: Machine learning has been used to develop predictive models to support clinicians in mak...

Examining the Use of an Artificial Intelligence Model to Diagnose Influenza: Development and Validation Study.

BACKGROUND: The global burden of influenza is substantial. It is a major disease that causes annual ...

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