AIMC Topic: Lung
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A Joint Classification Method for COVID-19 Lesions Based on Deep Learning and Radiomics.
Tomography (Ann Arbor, Mich.)
Sep 5, 2024
Pneumonia caused by novel coronavirus is an acute respiratory infectious disease. Its rapid spread in a short period of time has brought great challenges for global public health. The use of deep learning and radiomics methods can effectively disting...
Combining Multistaged Filters and Modified Segmentation Network for Improving Lung Nodules Classification.
IEEE journal of biomedical and health informatics
Sep 5, 2024
Advancements in computational technology have led to a shift towards automated detection processes in lung cancer screening, particularly through nodule segmentation techniques. These techniques employ thresholding to distinguish between soft and fir...
Use of artificial intelligence algorithms to analyse systemic sclerosis-interstitial lung disease imaging features.
Rheumatology international
Aug 29, 2024
The use of artificial intelligence (AI) in high-resolution computed tomography (HRCT) for diagnosing systemic sclerosis-associated interstitial lung disease (SSc-ILD) is relatively limited. This study aimed to analyse lung HRCT images of patients wit...
Heatstroke death identification using ATR-FTIR spectroscopy combined with a novel multi-organ machine learning approach.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Aug 27, 2024
With global warming, the number of deaths due to heatstroke has drastically increased. Nevertheless, there are still difficulties with the forensic assessment of heatstroke deaths, including the absence of particular organ pathological abnormalities ...
COVID-19 severity detection using chest X-ray segmentation and deep learning.
Scientific reports
Aug 27, 2024
COVID-19 has resulted in a significant global impact on health, the economy, education, and daily life. The disease can range from mild to severe, with individuals over 65 or those with underlying medical conditions being more susceptible to severe i...
Development and testing of a deep learning algorithm to detect lung consolidation among children with pneumonia using hand-held ultrasound.
PloS one
Aug 27, 2024
BACKGROUND AND OBJECTIVES: Severe pneumonia is the leading cause of death among young children worldwide, disproportionately impacting children who lack access to advanced diagnostic imaging. Here our objectives were to develop and test the accuracy ...
Quantitative CT Imaging Features Associated with Stable PRISm using Machine Learning.
Academic radiology
Aug 26, 2024
RATIONALE AND OBJECTIVES: The structural lung features that characterize individuals with preserved ratio impaired spirometry (PRISm) that remain stable overtime are unknown. The objective of this study was to use machine learning models with compute...
Artificial intelligence-driven automated lung sizing from chest radiographs.
American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons
Aug 23, 2024
Lung size measurements play an important role in transplantation, as optimal donor-recipient size matching is necessary to ensure the best possible outcome. Although several strategies for size matching are currently used, all have limitations, and n...
Improving Xenon-129 lung ventilation image SNR with deep-learning based image reconstruction.
Magnetic resonance in medicine
Aug 18, 2024
PURPOSE: To evaluate the feasibility and utility of a deep learning (DL)-based reconstruction for improving the SNR of hyperpolarized Xe lung ventilation MRI.
Artificial intelligence-driven volumetric CT outcome score in cystic fibrosis: longitudinal and multicenter validation with/without modulators treatment.
European radiology
Aug 16, 2024
OBJECTIVES: Holistic segmentation of CT structural alterations with 3D deep learning has recently been described in cystic fibrosis (CF), allowing the measurement of normalized volumes of airway abnormalities (NOVAA-CT) as an automated quantitative o...
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