OBJECTIVES: Current state-of-the-art natural language processing (NLP) techniques use transformer deep-learning architectures, which depend on large training datasets. We hypothesized that traditional NLP techniques may outperform transformers for sm...
Artificial intelligence (AI) and its machine learning (ML) algorithms are offering new promise for personalized biomedicine and more cost-effective healthcare with impressive technical capability to mimic human cognitive capabilities. However, widesp...
ChatGPT is a newly developed technology created by the OpenAI company. It is an artificial-intelligence-based large language model (LLM) and able to generate human-like text. The potential roles of ChatGPT in clinical decision support and academic wr...
OBJECTIVE: Gamma passing rate (GPR) predictions using machine learning methods have been explored for treatment verification of radiotherapy plans. However, these methods presented datasets with unbalanced number of plans having different treatment c...
OBJECTIVE: Accurate diagnosis and early treatment are crucial for survival in patients with brain metastases. This study aims to expand the capability of radiomics-based classification algorithms with novel features and compare results with deep lear...
The rapid growth of medical imaging has placed increasing demands on radiologists. In this scenario, artificial intelligence (AI) has become an attractive partner, one that may complement case interpretation and may aid in various non-interpretive as...
OBJECTIVE: As the number of radiology artificial intelligence (AI) papers increases, there are new challenges for reviewing the AI literature as well as differences to be aware of, for those familiar with the clinical radiology literature. We aim to ...
OBJECTIVE: To investigate the effectiveness of a deep learning model in helping radiologists or radiology residents detect esophageal cancer on contrast-enhanced CT images.
OBJECTIVES: To evaluate the feasibility of combining compressed sense (CS) with a newly developed deep learning-based algorithm (CS-AI) using convolutional neural networks to accelerate 2D MRI of the knee.
OBJECTIVE: To evaluate the performance and robustness of a deep learning-based automatic fresh rib fracture detection and positioning system (FRF-DPS).