AIMC Topic: Lung Diseases

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Exploring the assessment of post-cardiac valve surgery pulmonary complication risks through the integration of wearable continuous physiological and clinical data.

BMC medical informatics and decision making Jan 31, 2025
BACKGROUND: Postoperative pulmonary complications (PPCs) following cardiac valvular surgery are characterized by high morbidity, mortality, and economic cost. This study leverages wearable technology and machine learning algorithms to preoperatively ...
Machine Learning Prospective Studies Female Aged Humans Wearable Electronic Devices Lung Diseases Cardiac Surgical Procedures Heart Valves Male Middle Aged Risk Assessment Postoperative Complications
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AI-assisted detection for chest X-rays (AID-CXR): a multi-reader multi-case study protocol.

BMJ open Dec 20, 2024
INTRODUCTION: A chest X-ray (CXR) is the most common imaging investigation performed worldwide. Advances in machine learning and computer vision technologies have led to the development of several artificial intelligence (AI) tools to detect abnormal...
Radiography, Thoracic ROC Curve Radiographic Image Interpretation, Computer-Assisted Lung Diseases Humans Artificial Intelligence Algorithms Research Design Retrospective Studies
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CNN-O-ELMNet: Optimized Lightweight and Generalized Model for Lung Disease Classification and Severity Assessment.

IEEE transactions on medical imaging Dec 2, 2024
The high burden of lung diseases on healthcare necessitates effective detection methods. Current Computer-aided design (CAD) systems are limited by their focus on specific diseases and computationally demanding deep learning models. To overcome these...
Lung Diseases Image Interpretation, Computer-Assisted Humans Lung Neural Networks, Computer Severity of Illness Index Algorithms Deep Learning Lung Neoplasms
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Attention-based multi-residual network for lung segmentation in diseased lungs with custom data augmentation.

Scientific reports Nov 22, 2024
Lung disease analysis in chest X-rays (CXR) using deep learning presents significant challenges due to the wide variation in lung appearance caused by disease progression and differing X-ray settings. While deep learning models have shown remarkable ...
Humans COVID-19 SARS-CoV-2 Lung Deep Learning Pneumoconiosis Radiographic Image Interpretation, Computer-Assisted Lung Diseases Radiography, Thoracic
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A Physics-Informed Deep Neural Network for Harmonization of CT Images.

IEEE transactions on bio-medical engineering Nov 21, 2024
OBJECTIVE: Computed Tomography (CT) quantification is affected by the variability in image acquisition and rendition. This paper aimed to reduce this variability by harmonizing the images utilizing physics-based deep neural networks (DNNs).
Lung Diseases Phantoms, Imaging Lung Deep Learning Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted Neural Networks, Computer Algorithms Tomography, X-Ray Computed Humans
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Development of a simplified model and nomogram for the prediction of pulmonary hemorrhage in respiratory distress syndrome in extremely preterm infants.

BMC pediatrics Nov 21, 2024
BACKGROUND: Pulmonary hemorrhage (PH) in respiratory distress syndrome (RDS) in extremely preterm infants exhibits a high mortality rate and poor long-term outcomes. The aim of the present study was to develop a machine learning (ML) predictive model...
Male Machine Learning Infant, Extremely Premature Lung Diseases Retrospective Studies Nomograms Hemorrhage Humans Female Respiratory Distress Syndrome, Newborn Infant, Newborn
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Real-World evaluation of an AI triaging system for chest X-rays: A prospective clinical study.

European journal of radiology Oct 10, 2024
Chest X-rays (CXRs) are crucial for diagnosing and managing lung conditions. While CXR is a common and cost-effective diagnostic tool, interpreting the high volume of CXRs is challenging due to workforce limitations. Artificial intelligence (AI) offe...
Humans Artificial Intelligence Software Aged Aged, 80 and over Young Adult Adult Prospective Studies Female Reproducibility of Results Adolescent Triage Lung Diseases Sensitivity and Specificity Radiography, Thoracic Male Middle Aged
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Deep-learning model accurately classifies multi-label lung ultrasound findings, enhancing diagnostic accuracy and inter-reader agreement.

Scientific reports Sep 27, 2024
Despite the increasing use of lung ultrasound (LUS) in the evaluation of respiratory disease, operators' competence constrains its effectiveness. We developed a deep-learning (DL) model for multi-label classification using LUS and validated its perfo...
Lung Aged Humans Deep Learning Lung Diseases Adult Retrospective Studies Ultrasonography Observer Variation Female Male Middle Aged
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Integrating StEP-COMPAC definition and enhanced recovery after surgery status in a machine-learning-based model for postoperative pulmonary complications in laparoscopic hepatectomy.

Anaesthesia, critical care & pain medicine Sep 13, 2024
BACKGROUND: Postoperative pulmonary complications (PPCs) contribute to high mortality rates and impose significant financial burdens. In this study, a machine learning-based prediction model was developed to identify patients at high risk of developi...
Adult Male Middle Aged Postoperative Complications Enhanced Recovery After Surgery Retrospective Studies Laparoscopy Humans Female Machine Learning Lung Diseases Aged Hepatectomy
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Fuzzy lattices assisted EJAYA Q-learning for automated pulmonary diseases classification.

Biomedical physics & engineering express Sep 3, 2024
This work proposes a novel technique called Enhanced JAYA (EJAYA) assisted Q-Learning for the classification of pulmonary diseases, such as pneumonia and tuberculosis (TB) sub-classes using chest x-ray images. The work introduces Fuzzy lattices forma...
Fuzzy Logic Pneumonia Lung Diseases Tuberculosis Reproducibility of Results Sensitivity and Specificity Humans Image Processing, Computer-Assisted Machine Learning Algorithms
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