Pulmonology

A deep learning feature extraction-based hybrid approach for detecting pediatric pneumonia in chest X-ray images.

Pneumonia is a disease caused by bacteria, viruses, and fungi that settle in the alveolar sacs of the lungs and can lead to serious health complications in humans. Early detection of pneumonia is necessary for early treatment to manage and cure the disease. Recently, machine learning-based pneumonia detection methods have focused on pneumonia in adults. Machine learning relies on manual feature en...

Performance Analysis in Children of Traditional and Deep Learning CT Lung Nodule Computer-Aided Detection Systems Trained on Adults.

Although primary lung cancer is rare in children, chest CT is commonly performed to assess for lung metastases in children with cancer. Lung nodule computer-aided detection (CAD) systems have been designed and studied primarily using adult training data, and the efficacy of such systems when applied to pediatric patients is poorly understood. The purpose of this study was to evaluate in children...

Application of artificial intelligence techniques for non-alcoholic fatty liver disease diagnosis: A systematic review (2005-2023).

BACKGROUND AND OBJECTIVES: Non-alcoholic fatty liver disease (NAFLD) is a common liver disease with a rapidly growing incidence worldwide. For prognos...

Deep learning based automatic internal gross target volume delineation from 4D-CT of hepatocellular carcinoma patients.

BACKGROUND: The location and morphology of the liver are significantly affected by respiratory motion. Therefore, delineating the gross target volume ...

Novel Deep Learning Denoising Enhances Image Quality and Lowers Radiation Exposure in Interventional Bronchial Artery Embolization Cone Beam CT.

OBJECTIVES: In interventional bronchial artery embolization (BAE), periprocedural cone beam CT (CBCT) improves guiding and localization. However, a tr...

Exogenous Phytosulfokine α (PSKα) Alleviates Chilling Injury of Kiwifruit by Regulating Ca and Protein Kinase-Mediated Reactive Oxygen Species Metabolism.

Kiwifruit fruit stored at low temperatures are susceptible to chilling injury, leading to rapid softening, which therefore affects storage and marketi...

Real-time counting of wheezing events from lung sounds using deep learning algorithms: Implications for disease prediction and early intervention.

This pioneering study aims to revolutionize self-symptom management and telemedicine-based remote monitoring through the development of a real-time wh...

PET/CT based cross-modal deep learning signature to predict occult nodal metastasis in lung cancer.

Occult nodal metastasis (ONM) plays a significant role in comprehensive treatments of non-small cell lung cancer (NSCLC). This study aims to develop a...

Combined model integrating deep learning, radiomics, and clinical data to classify lung nodules at chest CT.

OBJECTIVES: The study aimed to develop a combined model that integrates deep learning (DL), radiomics, and clinical data to classify lung nodules into...

A deep learning LSTM-based approach for forecasting annual pollen curves: Olea and Urticaceae pollen types as a case study.

Airborne pollen can trigger allergic rhinitis and other respiratory diseases in the synthesised population, which makes it one of the most relevant bi...

Prediction and related genes of cancer distant metastasis based on deep learning.

Cancer metastasis is one of the main causes of cancer progression and difficulty in treatment. Genes play a key role in the process of cancer metastas...

Robotic retroperitoneal lymph node dissection for paratesticular rhabdomyosarcoma in adolescents: a case series.

Robotic assisted (RA) retroperitoneal lymph node dissection (RPLND) has grown in popularity as it offers decreased morbidity and faster recovery compa...

An Artificial Intelligence Platform for the Radiologic Diagnosis of Pulmonary Sarcoidosis: An Initial Pilot Study of Chest Computed Tomography Analysis to Distinguish Pulmonary Sarcoidosis from a Negative Lung Cancer Screening Scan.

PURPOSE: To determine the reliability of an artificial intelligence, deep learning (AI/DL)-based method of chest computer tomography (CT) scan analysi...

An extended focused assessment with sonography in trauma ultrasound tissue-mimicking phantom for developing automated diagnostic technologies.

Medical imaging-based triage is critical for ensuring medical treatment is timely and prioritized. However, without proper image collection and inter...

CT-Based Deep-Learning Model for Spread-Through-Air-Spaces Prediction in Ground Glass-Predominant Lung Adenocarcinoma.

BACKGROUND: Sublobar resection is strongly associated with poor prognosis in early-stage lung adenocarcinoma, with the presence of tumor spread throug...

Predicting multiple conformations via sequence clustering and AlphaFold2.

AlphaFold2 (ref. ) has revolutionized structural biology by accurately predicting single structures of proteins. However, a protein's biological funct...

Effect of multimodal diagnostic approach using deep learning-based automated detection algorithm for active pulmonary tuberculosis.

In this study, we developed a model to predict culture test results for pulmonary tuberculosis (PTB) with a customized multimodal approach and evaluat...

CT-derived pectoralis composition and incident pneumonia hospitalization using fully automated deep-learning algorithm: multi-ethnic study of atherosclerosis.

BACKGROUND: Pneumonia-related hospitalization may be associated with advanced skeletal muscle loss due to aging (i.e., sarcopenia) or chronic illnesse...

Advancing prognostic precision in pulmonary embolism: A clinical and laboratory-based artificial intelligence approach for enhanced early mortality risk stratification.

BACKGROUND: Acute pulmonary embolism (PE) is a critical medical emergency that necessitates prompt identification and intervention. Accurate prognosti...

How AI is advancing asthma management? Insights into economic and clinical aspects.

Asthma, an increasingly prevalent chronic respiratory condition, incurs significant economic costs worldwide. Artificial Intelligence (AI), particular...