Pulmonology

Research on Deep Learning Model of Feature Extraction Based on Convolutional Neural Network

Neural networks with relatively shallow layers and simple structures may have limited ability in accurately identifying pneumonia. In addition, deep neural networks also have a large demand for computing resources, which may cause convolutional neural networks to be unable to be implemented on terminals. Therefore, this paper will carry out the optimal classification of convolutional neural netw...

[Artificial intelligence research advances in discrimination and diagnosis of pulmonary ground-glass nodules].

Lung cancer, which accounts for about 18% of all cancer-related deaths worldwide, has a dismal 5-year survival rate of less than 20%. Survival rates for early-stage lung cancers (stages IA1, IA2, IA3, and IB, according to the TNM staging system) are significantly higher, underscoring the critical importance of early detection, diagnosis, and treatment. Ground-glass nodules (GGNs), which are common...

[Development of a grading diagnostic model for schistosomiasis-induced liver fibrosis based on radiomics and clinical laboratory indicators].

OBJECTIVE: To investigate the feasibility of developing a grading diagnostic model for schistosomiasis-induced liver fibrosis based on B-mode ultrason...

Dog Heart Rate and Blood Oxygen Metaverse Interaction System

This study developed an improved dog heart rate and blood oxygen sensor system using Arduino. Traditional methods face accuracy and reliability issu...

A back propagation neural network based respiratory motion modelling method.

BACKGROUND: This study presents the development of a backpropagation neural network-based respiratory motion modelling method (BP-RMM) for precisely t...

Arrhythmic Mitral Valve Prolapse Phenotype: An Unsupervised Machine Learning Analysis Using a Multicenter Cardiac MRI Registry.

Purpose To use unsupervised machine learning to identify phenotypic clusters with increased risk of arrhythmic mitral valve prolapse (MVP). Materials ...

Improving Prediction of Survival and Progression in Metastatic Non-Small Cell Lung Cancer After Immunotherapy Through Machine Learning of Circulating Tumor DNA.

PURPOSE: To use modern machine learning approaches to enhance and automate the feature extraction from the longitudinal circulating tumor DNA (ctDNA) ...

Assessing the readability, reliability, and quality of artificial intelligence chatbot responses to the 100 most searched queries about cardiopulmonary resuscitation: An observational study.

This study aimed to evaluate the readability, reliability, and quality of responses by 4 selected artificial intelligence (AI)-based large language mo...

A SARS-CoV-2 Interaction Dataset and VHH Sequence Corpus for Antibody Language Models

Antibodies are crucial proteins produced by the immune system to eliminate harmful foreign substances and have become pivotal therapeutic agents for...

Exploring Negated Entites for Named Entity Recognition in Italian Lung Cancer Clinical Reports.

This paper explores the potential of leveraging electronic health records (EHRs) for personalized health research through the application of artificia...

SPIN: sex-specific and pathway-based interpretable neural network for sexual dimorphism analysis.

Sexual dimorphism in prevalence, severity and genetic susceptibility exists for most common diseases. However, most genetic and clinical outcome studi...

Mutation prediction in the SARS-CoV-2 genome using attention-based neural machine translation.

Severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) has been evolving rapidly after causing havoc worldwide in 2020. Since then, it has been ...

Omics-based deep learning approaches for lung cancer decision-making and therapeutics development.

Lung cancer has been the most common and the leading cause of cancer deaths globally. Besides clinicopathological observations and traditional molecul...

Validation of a machine learning algorithm to identify pulmonary vein isolation during ablation procedures for the treatment of atrial fibrillation: results of the PVISION study.

AIMS: Pulmonary vein isolation (PVI) is the cornerstone of ablation for atrial fibrillation. Confirmation of PVI can be challenging due to the presenc...

Deep Learning Classification of Usual Interstitial Pneumonia Predicts Outcomes.

Computed tomography (CT) enables noninvasive diagnosis of usual interstitial pneumonia (UIP), but enhanced image analyses are needed to overcome the ...

Assistive AI in Lung Cancer Screening: A Retrospective Multinational Study in the United States and Japan.

Purpose To evaluate the impact of an artificial intelligence (AI) assistant for lung cancer screening on multinational clinical workflows. Materials a...

AI serves up target and inhibitor for lung fibrosis.

An open auscultation dataset for machine learning-based respiratory diagnosis studies.

Machine learning enabled auscultating diagnosis can provide promising solutions especially for prescreening purposes. The bottleneck for its potential...

Clinical Validation of Artificial Intelligence-Powered PD-L1 Tumor Proportion Score Interpretation for Immune Checkpoint Inhibitor Response Prediction in Non-Small Cell Lung Cancer.

PURPOSE: Evaluation of PD-L1 tumor proportion score (TPS) by pathologists has been very impactful but is limited by factors such as intraobserver/inte...

Establishment and validation of multiclassification prediction models for pulmonary nodules based on machine learning.

BACKGROUND: Lung cancer is the leading cause of cancer-related death worldwide. This study aimed to establish novel multiclassification prediction mod...