AIMC Topic: Lung
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A user-friendly deep learning application for accurate lung cancer diagnosis.
Journal of X-ray science and technology
Jan 1, 2024
BACKGROUND: Accurate diagnosis and subsequent delineated treatment planning require the experience of clinicians in the handling of their case numbers. However, applying deep learning in image processing is useful in creating tools that promise faste...
Artificial Intelligence in Lung Cancer Imaging: From Data to Therapy.
Critical reviews in oncogenesis
Jan 1, 2024
Lung cancer remains a global health challenge, leading to substantial morbidity and mortality. While prevention and early detection strategies have improved, the need for precise diagnosis, prognosis, and treatment remains crucial. In this comprehens...
Evaluation of Interstitial Lung Diseases with Deep Learning Method of Two Major Computed Tomography Patterns.
Current medical imaging
Jan 1, 2024
BACKGROUND: Interstitial lung diseases (ILD) encompass various disorders characterized by inflammation and/or fibrosis in the lung interstitium. These conditions produce distinct patterns in High-Resolution Computed Tomography (HRCT).
A Novel Approach to the Technique of Lung Region Segmentation Based on a Deep Learning Model to Diagnose COVID-19 X-ray Images.
Current medical imaging
Jan 1, 2024
BACKGROUND: The novel coronavirus pandemic has caused a global health crisis, placing immense strain on healthcare systems worldwide. Chest X-ray technology has emerged as a critical tool for the diagnosis and treatment of COVID-19. However, the manu...
Chest CT Image based Lung Disease Classification - A Review.
Current medical imaging
Jan 1, 2024
Computed tomography (CT) scans are widely used to diagnose lung conditions due to their ability to provide a detailed overview of the body's respiratory system. Despite its popularity, visual examination of CT scan images can lead to misinterpretatio...
Severity-stratification of interstitial lung disease by deep learning enabled assessment and quantification of lesion indicators from HRCT images.
Journal of X-ray science and technology
Jan 1, 2024
BACKGROUND: Interstitial lung disease (ILD) represents a group of chronic heterogeneous diseases, and current clinical practice in assessment of ILD severity and progression mainly rely on the radiologist-based visual screening, which greatly restric...
Comparison of Commercial AI Software Performance for Radiograph Lung Nodule Detection and Bone Age Prediction.
Radiology
Jan 1, 2024
Background Multiple commercial artificial intelligence (AI) products exist for assessing radiographs; however, comparable performance data for these algorithms are limited. Purpose To perform an independent, stand-alone validation of commercially ava...
Optimizing Computer-Aided Diagnosis with Cost-Aware Deep Learning Models.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2024
Classical machine learning and deep learning models for Computer-Aided Diagnosis (CAD) commonly focus on overall classification performance, treating misclassification errors (false negatives and false positives) equally during training. This uniform...
[Advances in chest imaging in early chronic obstructive pulmonary disease].
Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases
Dec 12, 2023
Chronic obstructive pulmonary disease(COPD)is a heterogeneous and complex disease, and is characterized by exertional dyspnea and chronic cough. For many years, lung function testing have been used to diagnose COPD, but the sensitivity of lung functi...
Clinical Study of Artificial Intelligence in Imaging Diagnosis of False Positive Lesions of Pulmonary Nodules.
Journal of the College of Physicians and Surgeons--Pakistan : JCPSP
Oct 1, 2023
OBJECTIVE: To determine the accuracy of diagnosis of pulmonary nodules using artificial intelligence method.
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