Oral surgery, oral medicine, oral pathology and oral radiology
Mar 30, 2023
OBJECTIVES: We aimed to develop an artificial intelligence-based clinical dental decision-support system using deep-learning methods to reduce diagnostic interpretation error and time and increase the effectiveness of dental treatment and classificat...
Deep learning has led to incredible breakthroughs in areas of research, from self-driving vehicles to solutions, to formal mathematical proofs. In the biomedical sciences, however, the revolutionary results seen in other fields are only now beginning...
Journal of assisted reproduction and genetics
Mar 30, 2023
PURPOSE: Rapid and easy detection of spermatogonial stem/progenitor cells (SSPCs) is crucial for clinicians dealing with male infertility caused by prepubertal testicular damage. Deep learning (DL) methods may offer visual tools for tracking SSPCs on...
Macular OCT angiography (OCTA) measurements have been reported to be useful for glaucoma diagnostics. However, research on highly myopic glaucoma is lacking, and the diagnostic value of macular OCTA measurements versus OCT parameters remains inconclu...
Restorative environments help people recover from mental fatigue and negative emotional and physical reactions to stress. Excellent restorative environments in urban streets help people focus and improve their daily behavioral performance, allowing t...
Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
Mar 29, 2023
PURPOSE: To compare the effects of deep learning reconstruction (DLR) on respiratory-triggered T2-weighted MRI of the liver between single-shot fast spin-echo (SSFSE) and fast spin-echo (FSE) sequences.
OBJECTIVES: The objective of this study was to translate a deep learning (DL) approach for semiautomated analysis of body composition (BC) measures from standard of care CT images to investigate the prognostic value of BC in pediatric, adolescent, an...
The current artificial intelligence (AI) models are still insufficient in multi-disease diagnosis for real-world data, which always present a long-tail distribution. To tackle this issue, a long-tail public dataset, "ChestX-ray14," which involved fou...
PURPOSE: Deep learning (DL) is a state-of-the-art technique for developing artificial intelligence in various domains and it improves the performance of natural language processing (NLP). Therefore, we aimed to develop a DL-based NLP model that class...
For automatic EEG diagnosis, this paper presents a new EEG data set with well-organized clinical annotations called Chung-Ang University Hospital EEG (CAUEEG), which has event history, patient's age, and corresponding diagnosis labels. We also design...
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