Pulmonology

Development and validation of an early diagnosis model for severe mycoplasma pneumonia in children based on interpretable machine learning.

BACKGROUND: Pneumonia is a major threat to the health of children, especially those under the age of five. Mycoplasma  pneumoniae infection is a core cause of pediatric pneumonia, and the incidence of severe mycoplasma pneumoniae pneumonia (SMPP) has increased in recent years. Therefore, there is an urgent need to establish an early warning model for SMPP to improve the prognosis of pediatric pneu...

Lightweight and universal deep learning model for fast proton spot dose calculation at arbitrary energies.

To better integrate into processes like rapid adaptive planning and quality assurance, this study aims to propose a lightweight and universal proton spot dose calculation model suitable for arbitrary energies.Given the alignment between the characteristics of proton spot dose deposition and the sequence learning capabilities of the long short-term memory (LSTM) network, the lightweight model, mult...

Characteristics of lung sounds in early infants using automated analysis.

UNLABELLED: A new lung sound analysis software program has been developed. It can automatically select a typical lung sound spectrogram and calculate ...

AI-Based Quantitative CT Analysis of Temporal Changes According to Disease Severity in COVID-19 Pneumonia.

OBJECTIVE: To quantitatively evaluate computed tomography (CT) parameters of coronavirus disease 2019 (COVID-19) pneumonia an artificial intelligence ...

Use of a Dual Artificial Intelligence Platform to Detect Unreported Lung Nodules.

OBJECTIVE: To investigate the performance of Dual-AI Deep Learning Platform in detecting unreported pulmonary nodules that are 6 mm or greater, compri...

[Chest radiological lesions in COVID-19 : from classical imaging to artificial intelligence].

In the course of the pandemic induced by the appearance of a new coronavirus (SARS-CoV-2; COVID-19) causing acute respiratory distress syndrome (ARDS)...

AI-Enabled Accurate Non-Invasive Assessment of Pulmonary Hypertension Progression via Multi-Modal Echocardiography

Echocardiographers can detect pulmonary hypertension using Doppler echocardiography; however, accurately assessing its progression often proves chal...

Piezoelectret Textile Dressing for Biosignal Monitored Wound Healing.

In recent years, smart textile sensors have gained exponential growth in various sectors such as wearable technology and healthcare. However, addressi...

GAMMNet: Gating Multi-head Attention in a Multi-modal Deep Network for Sound Based Respiratory Disease Detection.

Respiratory diseases present significant challenges to global health due to their high morbidity and mortality rates. Traditional diagnostic methods, ...

Two-Stage Automatic Liver Classification System Based on Deep Learning Approach Using CT Images.

Alveolar echinococcosis (AE) is a parasitic disease caused by Echinococcus multilocularis, where early detection is crucial for effective treatment. T...

OptLung: An online predictive model for optimizing therapeutic strategies for second primary lung cancer in cancer survivors.

BACKGROUND: Advances in cancer detection and treatment have significantly improved survival rates and led to an increasing prevalence of the second pr...

Prognostic Value of the Brixia Radiological Score in COVID-19 Patients: A Retrospective Study from Romania.

The novel coronavirus pandemic, SARS-CoV-2, has a variable clinical spectrum, ranging from asymptomatic to critical forms. High mortality and morbidit...

Predictive machine learning algorithm for COPD exacerbations using a digital inhaler with integrated sensors.

PURPOSE: By using data obtained with digital inhalers, machine learning models have the potential to detect early signs of deterioration and predict i...

Developing muscarinic receptor M1 classification models utilizing transfer learning and generative AI techniques.

Muscarinic receptor subtype 1 (M1) is a G protein-coupled receptor (GPCR) and a key pharmacological target for peripheral neuropathy, chronic obstruct...

A systematic review and meta-analysis of lung cancer risk prediction models.

BACKGROUND: Lung cancer (LC) remains the leading cause of cancer-related mortality worldwide. Early detection through targeted screening significantly...

[Pulmonary vascular interventions: innovating through adaptation and advancing through differentiation].

Pulmonary vascular intervention technology, with its minimally invasive and precise advantages, has been a groundbreaking advancement in the treatment...

Real-world Evaluation of Computer-aided Pulmonary Nodule Detection Software Sensitivity and False Positive Rate.

PURPOSE: Evaluate the false positive rate (FPR) of nodule detection software in real-world use.

Efficient and Robust Multidimensional Attention in Remote Physiological Sensing through Target Signal Constrained Factorization

Remote physiological sensing using camera-based technologies offers transformative potential for non-invasive vital sign monitoring across healthcar...

Promptable segmentation of CT lung lesions based on improved U-Net and Segment Anything model (SAM).

BackgroundComputed tomography (CT) is widely used in clinical diagnosis of lung diseases. The automatic segmentation of lesions in CT images aids in t...

Prescriptive analytics decision-making system for cardiovascular disease prediction in long COVID patients using advanced reinforcement learning algorithms.

In recent years Covid-19 impact is causing unprecedented difficulties worldwide, affecting lifestyle choices. The post-pandemic era has made this even...