Pulmonology

Longitudinal Assessment of Lung Lesion Burden in CT

In the U.S., lung cancer is the second major cause of death. Early detection of suspicious lung nodules is crucial for patient treatment planning, management, and improving outcomes. Many approaches for lung nodule segmentation and volumetric analysis have been proposed, but few have looked at longitudinal changes in total lung tumor burden. In this work, we trained two 3D models (nnUNet) with a...

Hybrid CNN with Chebyshev Polynomial Expansion for Medical Image Analysis

Lung cancer remains one of the leading causes of cancer-related mortality worldwide, with early and accurate diagnosis playing a pivotal role in improving patient outcomes. Automated detection of pulmonary nodules in computed tomography (CT) scans is a challenging task due to variability in nodule size, shape, texture, and location. Traditional Convolutional Neural Networks (CNNs) have shown con...

MedGNN: Capturing the Links Between Urban Characteristics and Medical Prescriptions

Understanding how urban socio-demographic and environmental factors relate with health is essential for public health and urban planning. However, t...

Leveraging Gait Patterns as Biomarkers: An attention-guided Deep Multiple Instance Learning Network for Scoliosis Classification

Scoliosis is a spinal curvature disorder that is difficult to detect early and can compress the chest cavity, impacting respiratory function and car...

Low-cost Embedded Breathing Rate Determination Using 802.15.4z IR-UWB Hardware for Remote Healthcare

Respiratory diseases account for a significant portion of global mortality. Affordable and early detection is an effective way of addressing these a...

Graph Classification and Radiomics Signature for Identification of Tuberculous Meningitis

Introduction: Tuberculous meningitis (TBM) is a serious brain infection caused by Mycobacterium tuberculosis, characterized by inflammation of the m...

Audio-based digital biomarkers in diagnosing and managing respiratory diseases: a systematic review and bibliometric analysis.

Advances in wearable sensors and artificial intelligence have greatly enhanced the potential of digitised audio biomarkers for disease diagnostics and...

Artificial intelligence in bronchoscopy: a systematic review.

BACKGROUND: Artificial intelligence (AI) systems have been implemented to improve the diagnostic yield and operators' skills within endoscopy. Similar...

Effect of adaptive statistical iterative reconstruction-V algorithm and deep learning image reconstruction algorithm on image quality and emphysema quantification in COPD patients under ultra-low-dose conditions.

PURPOSE: To explore the effect of different reconstruction algorithms (ASIR-V and DLIR) on image quality and emphysema quantification in chronic obstr...

Deep Learning-Based Computer-Aided Diagnosis in Coronary Artery Calcium-Scoring CT for Pulmonary Nodule Detection: A Preliminary Study.

PURPOSE: To evaluate the feasibility and utility of deep learning-based computer-aided diagnosis (DL-CAD) for the detection of pulmonary nodules on co...

MoLPre: A Machine Learning Model to Predict Metastasis of cT1 Solid Lung Cancer.

Given that more than 20% of patients with cT1 solid NSCLC showed nodal or extrathoracic metastasis, early detection of metastasis is crucial and urgen...

Machine Learning Unveils Sphingolipid Metabolism's Role in Tumour Microenvironment and Immunotherapy in Lung Cancer.

TME is a core player in the development of a cancerous lesion, the immune evasive potential of the lesion, and its response to therapy. Sphingolipid m...

PD-L1 Scoring Models for Non-Small Cell Lung Cancer in China: Current Status, AI-Assisted Solutions and Future Perspectives.

Immunotherapy has revolutionized the diagnosis and treatment model for patients with advanced non-small cell lung cancer (NSCLC). Numerous clinical tr...

Utilizing Machine Learning to Predict Liver Allograft Fibrosis by Leveraging Clinical and Imaging Data.

BACKGROUND AND AIM: Liver transplant (LT) recipients may succumb to graft-related pathologies, contributing to graft fibrosis (GF). Current methods to...

Deep Learning Model for Diagnosing and Classifying Subtypes of Chronic Pulmonary Aspergillosis in Chest CT.

BACKGROUND: Diagnosing chronic pulmonary aspergillosis (CPA) and its subtypes is essential for treatment and prognosis. In clinical practice, inexperi...

Automated Bi-Ventricular Segmentation and Regional Cardiac Wall Motion Analysis for Rat Models of Pulmonary Hypertension.

Artificial intelligence-based cardiac motion mapping offers predictive insights into pulmonary hypertension (PH) disease progression and its impact on...

Predicting Targeted Therapy Resistance in Non-Small Cell Lung Cancer Using Multimodal Machine Learning

Lung cancer is the primary cause of cancer death globally, with non-small cell lung cancer (NSCLC) emerging as its most prevalent subtype. Among NSC...

An Explainable Neural Radiomic Sequence Model with Spatiotemporal Continuity for Quantifying 4DCT-based Pulmonary Ventilation

Accurate evaluation of regional lung ventilation is essential for the management and treatment of lung cancer patients, supporting assessments of pu...

Diagnosis of Pulmonary Hypertension by Integrating Multimodal Data with a Hybrid Graph Convolutional and Transformer Network

Early and accurate diagnosis of pulmonary hypertension (PH) is essential for optimal patient management. Differentiating between pre-capillary and p...

X$^{2}$-Gaussian: 4D Radiative Gaussian Splatting for Continuous-time Tomographic Reconstruction

Four-dimensional computed tomography (4D CT) reconstruction is crucial for capturing dynamic anatomical changes but faces inherent limitations from ...