[Studies and Real-World Experience Regarding the Clinical Application of Artificial Intelligence Software for Lung Nodule Detection].
Junghoon KimPublished in: Journal of the Korean Society of Radiology (2024)
This article discusses studies and real-world experiences related to the clinical application of artificial intelligence-based computer-aided detection (AI-CAD) software (LuCAS-plus, Monitor Corporation) in detecting pulmonary nodules. During clinical trials for lung cancer screening, AI-CAD exhibited performance comparable to that of medical professionals in terms of sensitivity and specificity. Studies revealed that applying AI-CAD for diagnosing pulmonary metastases led to high detection rates. The use of a nodule matching algorithm in diagnosing pulmonary metastases significantly reduced false non-metastasis results. In clinical settings, implementing AI-CAD enhanced the efficiency of pulmonary nodule detection, saving time and effort during CT reading. Overall, AI-CAD is expected to offer substantial support for lung cancer screening and the interpretation of chest CT scans for malignant tumor surveillance.
Keyphrases
- open label
- artificial intelligence
- clinical trial
- machine learning
- deep learning
- big data
- coronary artery disease
- pulmonary hypertension
- loop mediated isothermal amplification
- computed tomography
- real time pcr
- label free
- contrast enhanced
- public health
- case control
- image quality
- randomized controlled trial
- mental health
- dual energy
- single cell
- positron emission tomography
- quality improvement
- pet ct
- data analysis