Pulmonology

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

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2D ultrasound imaging based intra-fraction respiratory motion tracking for abdominal radiation therapy using machine learning.

We have previously developed a robotic ultrasound imaging system for motion monitoring in abdominal ...

Toward predicting the evolution of lung tumors during radiotherapy observed on a longitudinal MR imaging study via a deep learning algorithm.

PURPOSE: To predict the spatial and temporal trajectories of lung tumor during radiotherapy monitore...

A large cohort study identifying a novel prognosis prediction model for lung adenocarcinoma through machine learning strategies.

BACKGROUND: Predicting lung adenocarcinoma (LUAD) risk is crucial in determining further treatment s...

Long-term follow-up of persistent pulmonary pure ground-glass nodules with deep learning-assisted nodule segmentation.

OBJECTIVE: To investigate the natural history of persistent pulmonary pure ground-glass nodules (pGG...

Predicting lung nodule malignancies by combining deep convolutional neural network and handcrafted features.

To predict lung nodule malignancy with a high sensitivity and specificity for low dose CT (LDCT) lun...

Weakly Supervised Deep Learning for Whole Slide Lung Cancer Image Analysis.

Histopathology image analysis serves as the gold standard for cancer diagnosis. Efficient and precis...

Deep learning with ultrasonography: automated classification of liver fibrosis usingĀ a deepĀ convolutional neural network.

OBJECTIVES: The aim of this study was to develop a deep convolutional neural network (DCNN) for the ...

Heat Flux Sensing for Machine-Learning-Based Personal Thermal Comfort Modeling.

In recent years, physiological features have gained more attention in developing models of personal ...

DeepOrganNet: On-the-Fly Reconstruction and Visualization of 3D / 4D Lung Models from Single-View Projections by Deep Deformation Network.

This paper introduces a deep neural network based method, i.e., DeepOrganNet, to generate and visual...

Machine-learning algorithms to identify key biosecurity practices and factors associated with breeding herds reporting PRRS outbreak.

Investments in biosecurity practices are made by producers to reduce the likelihood of introducing p...

Cross-modality (CT-MRI) prior augmented deep learning for robust lung tumor segmentation from small MR datasets.

PURPOSE: Accurate tumor segmentation is a requirement for magnetic resonance (MR)-based radiotherapy...

Localizing B-Lines in Lung Ultrasonography by Weakly Supervised Deep Learning, In-Vivo Results.

Lung ultrasound (LUS) is nowadays gaining growing attention from both the clinical and technical wor...

Classification of Volumetric Images Using Multi-Instance Learning and Extreme Value Theorem.

Volumetric imaging is an essential diagnostic tool for medical practitioners. The use of popular tec...

Automatic Pulmonary Nodule Detection in CT Scans Using Convolutional Neural Networks Based on Maximum Intensity Projection.

Accurate pulmonary nodule detection is a crucial step in lung cancer screening. Computer-aided detec...

Multi-Task Deep Model With Margin Ranking Loss for Lung Nodule Analysis.

Lung cancer is the leading cause of cancer deaths worldwide and early diagnosis of lung nodule is of...

Lung segmentation method with dilated convolution based on VGG-16 network.

Lung cancer has become one of the life-threatening killers. Lung disease need to be assisted by CT i...

An investigation of CNN models for differentiating malignant from benign lesions using small pathologically proven datasets.

Cancer has been one of the most threatening diseases to human health. There have been many efforts d...

A Real-Time Health 4.0 Framework with Novel Feature Extraction and Classification for Brain-Controlled IoT-Enabled Environments.

In this letter, we propose two novel methods for four-class motor imagery (MI) classification using ...

SecProMTB: Support Vector Machine-Based Classifier for Secretory Proteins Using Imbalanced Data Sets Applied to Mycobacterium tuberculosis.

Secretory proteins of Mycobacterium tuberculosis have created more concern, given their dominant imm...

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