Pulmonology

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

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Advanced hybrid attention-based deep learning network with heuristic algorithm for adaptive CT and PET image fusion in lung cancer detection.

Lung cancer is one of the most deadly diseases in the world. Lung cancer detection can save the pati...

BREATH-Net: a novel deep learning framework for NO prediction using bi-directional encoder with transformer.

Air pollution poses a significant challenge in numerous urban regions, negatively affecting human we...

LGDNet: local feature coupling global representations network for pulmonary nodules detection.

Detection of suspicious pulmonary nodules from lung CT scans is a crucial task in computer-aided dia...

Feasibility of the application of deep learning-reconstructed ultra-fast respiratory-triggered T2-weighted imaging at 3 T in liver imaging.

OBJECTIVE: The evaluate the feasibility of a novel deep learning-reconstructed ultra-fast respirator...

Transformaer-based model for lung adenocarcinoma subtypes.

BACKGROUND: Lung cancer has the highest morbidity and mortality rate among all types of cancer. Hist...

Deep Learning Radiomics Analysis of CT Imaging for Differentiating Between Crohn's Disease and Intestinal Tuberculosis.

This study aimed to develop and evaluate a CT-based deep learning radiomics model for differentiatin...

A Hybrid Framework of Dual-Domain Signal Restoration and Multi-depth Feature Reinforcement for Low-Dose Lung CT Denoising.

Low-dose computer tomography (LDCT) has been widely used in medical diagnosis. Various denoising met...

Improving Image Quality and Nodule Characterization in Ultra-low-dose Lung CT with Deep Learning Image Reconstruction.

RATIONALE AND OBJECTIVE: To investigate the influence of the deep learning image reconstruction (DLI...

Deep learning segmentation and registration-driven lung parenchymal volume and movement CT analysis in prone positioning.

PURPOSE: To conduct a volumetric and movement analysis of lung parenchyma in prone positioning using...

PulmoNet: a novel deep learning based pulmonary diseases detection model.

Pulmonary diseases are various pathological conditions that affect respiratory tissues and organs, m...

Artificial intelligence-based model for predicting pulmonary arterial hypertension on chest x-ray images.

BACKGROUND: Pulmonary arterial hypertension is a serious medical condition. However, the condition i...

ToxMPNN: A deep learning model for small molecule toxicity prediction.

Machine learning (ML) has shown a great promise in predicting toxicity of small molecules. However, ...

Multicentre validation of a machine learning model for predicting respiratory failure after noncardiac surgery.

BACKGROUND: Postoperative respiratory failure is a serious complication that could benefit from earl...

Deep match: A zero-shot framework for improved fiducial-free respiratory motion tracking.

BACKGROUND AND PURPOSE: Motion management is essential to reduce normal tissue exposure and maintain...

Biochemical implications of robotic surgery: a new frontier in the operating room.

Robotic surgery represents a milestone in surgical procedures, offering advantages such as less inva...

Clinical utilization of artificial intelligence in predicting therapeutic efficacy in pulmonary tuberculosis.

Traditional methods for monitoring pulmonary tuberculosis (PTB) treatment efficacy lack sensitivity,...

An Accelerometer-Based Wearable Patch for Robust Respiratory Rate and Wheeze Detection Using Deep Learning.

Wheezing is a critical indicator of various respiratory conditions, including asthma and chronic obs...

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