A systematic review of artificial intelligence tools for chronic pulmonary embolism on CT pulmonary angiography.
Lojain AbdulaalAhmed MaiterMahan SalehiMichael SharkeyTurki AlnasserPankaj GargSmitha RajaramCatherine HillChristopher JohnsAlex Matthew Knox RothmanKrit DwivediDavid G KielySamer AlabedAndrew James SwiftPublished in: Frontiers in radiology (2024)
In contrast to AI tools for evaluation of acute PE, there has been limited investigation of AI-based approaches to characterising chronic PE and CTEPH on CTPA. Existing studies are limited by inconsistent reporting of the data used to train and test their models. This systematic review highlights an area of potential expansion for the field of AI in medical image interpretation.There is limited knowledge of A systematic review of artificial intelligence tools for chronic pulmonary embolism in CT. This systematic review provides an assessment on research that examined deep learning algorithms in detecting CTEPH on CTPA images, the number of studies assessing the utility of deep learning on CTPA in CTEPH was unclear and should be highlighted.
Keyphrases
- artificial intelligence
- deep learning
- pulmonary embolism
- systematic review
- big data
- machine learning
- convolutional neural network
- inferior vena cava
- computed tomography
- meta analyses
- healthcare
- contrast enhanced
- image quality
- drug induced
- liver failure
- dual energy
- magnetic resonance
- pulmonary hypertension
- optical coherence tomography
- positron emission tomography
- magnetic resonance imaging
- emergency department
- intensive care unit
- climate change
- risk assessment
- case control
- respiratory failure
- mechanical ventilation
- acute respiratory distress syndrome
- pet ct