The international journal of cardiovascular imaging
Jul 30, 2018
To explore the diagnostic performance of a machine-learning-based (ML-based) computed fractional flow reserve (cFFR) derived from coronary computed tomography angiography (CCTA) in identifying ischemia-causing lesions verified by invasive FFR in cath...
We developed a computer-aided diagnosis (CADx) method for classification between benign nodule, primary lung cancer, and metastatic lung cancer and evaluated the following: (i) the usefulness of the deep convolutional neural network (DCNN) for CADx o...
OBJECTIVE: Application of machine learning techniques for automatic and reliable classification of clinical documents have shown promising results. However, machine learning models require abundant training data specific to each target hospital and m...
Artificial intelligence (AI) is already widely employed in various medical roles, and ongoing technological advances are encouraging more widespread use of AI in imaging. This is partly driven by the recognition of the significant frequency and clini...
Colorectal cancer is the fourth leading cause of cancer deaths worldwide and the second leading cause in the United States. The risk of colorectal cancer can be mitigated by the identification and removal of premalignant lesions through optical colon...
IEEE journal of biomedical and health informatics
May 29, 2018
Predicting malignant potential is one of the most critical components of a computer-aided diagnosis system for gastrointestinal stromal tumors (GISTs). These tumors have been studied only on the basis of subjective computed tomography findings. Among...
AJR. American journal of roentgenology
May 24, 2018
OBJECTIVE: The purpose of this study is to evaluate the diagnostic performance of machine learning techniques for malignancy prediction at breast cone-beam CT (CBCT) and to compare them to human readers.
The prerequisite for establishing an effective prediction system for mammographic diagnosis is the annotation of each mammographic image. The manual annotation work is time-consuming and laborious, which becomes a great hindrance for researchers. In ...
Inspired by gestalt psychology, we combine human cognitive characteristics with knowledge of radiologists in medical image analysis. In this paper, a novel framework is proposed to detect breast masses in digitized mammograms. It can be divided into ...
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