RATIONALE AND OBJECTIVES: To explore the classification and prediction efficacy of the deep learning model for benign prostate lesions, non-clinically significant prostate cancer (non-csPCa) and clinically significant prostate cancer (csPCa) in Prost...
BACKGROUND: In boron neutron capture therapy (BNCT)-a form of binary radiotherapy-the primary challenge in treatment planning systems for dose calculations arises from the time-consuming nature of the Monte Carlo (MC) method. Recent progress, includi...
PURPOSE: Nearly all published ophthalmology-related Big Data studies rely exclusively on International Classification of Diseases (ICD) billing codes to identify patients with particular ocular conditions. However, inaccurate or nonspecific codes may...
PURPOSE: The purpose of this study was to determine the utility of compressed sensing (CS) with deep learning reconstruction (DLR) for improving spatial resolution, image quality and focal liver lesion detection on high-resolution contrast-enhanced T...
In healthcare, artificial intelligence (AI) is expected to improve work processes, yet most research focuses on the technical features of AI rather than its real-world clinical implementation. To evaluate the implementation process of an AI-based com...
BACKGROUND: Chat generative retrained transformer (ChatGPT) represents a groundbreaking advancement in Artificial Intelligence (AI-chatbot) technology, utilizing transformer algorithms to enhance natural language processing and facilitating their use...
Medical & biological engineering & computing
Feb 1, 2024
In this paper, we propose a new robust and fast learning technique by investigating the effect of integration of quaternion and interval type II fuzzy logic along with non-iterative, parameter free deterministic learning machine (DLM) pertaining to f...
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