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Neural correlates of the uncanny valley effect for robots and hyper-realistic masks.
PloS one
Mar 18, 2025
Viewing artificial objects and images that are designed to appear human can elicit a sense of unease, referred to as the 'uncanny valley' effect. Here we investigate neural correlates of the uncanny valley, using still images of androids (robots desi...
Human-in-the-Loop Myoelectric Pattern Recognition Control of an Arm-Support Robot to Improve Reaching in Stroke Survivors.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Mar 18, 2025
The objective of this study was to assess the feasibility and efficacy of using real-time human-in-the-loop pattern recognition-based myoelectric control to control vertical support force or vertical position to improve reach in individuals with chro...
Improving Acceptance to Sensory Substitution: A Study on the V2A-SS Learning Model Based on Information Processing Learning Theory.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Mar 18, 2025
The visual sensory organ (VSO) serves as the primary channel for transmitting external information to the brain; therefore, damage to the VSO can severely limit daily activities. Visual-to-Auditory Sensory Substitution (V2A-SS), an innovative approac...
Visualized hysteroscopic artificial intelligence fertility assessment system for endometrial injury: an image-deep-learning study.
Annals of medicine
Mar 17, 2025
OBJECTIVE: Asherman's syndrome (AS) is a significant cause of subfertility in women from developing countries. Over 80% of AS cases in these regions are linked to dilation and curettage (D&C) procedures following pregnancy. The incidence of AS in pat...
Automatic bone age assessment: a Turkish population study.
Diagnostic and interventional radiology (Ankara, Turkey)
Mar 17, 2025
PURPOSE: Established methods for bone age assessment (BAA), such as the Greulich and Pyle atlas, suffer from variability due to population differences and observer discrepancies. Although automated BAA offers speed and consistency, limited research e...
Comparing two deep learning spectral reconstruction levels for abdominal evaluation using a rapid-kVp-switching dual-energy CT scanner.
Abdominal radiology (New York)
Mar 17, 2025
PURPOSE: Deep Learning Spectral Reconstruction (DLSR) potentially improves dual-energy CT (DECT) image quality, but there is a paucity of research involving human abdominal DECT scans. The purpose of this study was to comprehensively evaluate image q...
Diagnosis of moderate-to-severe hepatic steatosis using deep learning-based automated attenuation measurements on contrast-enhanced CT.
Abdominal radiology (New York)
Mar 17, 2025
PURPOSE: To evaluate the utility of deep learning-based automated attenuation measurements on contrast-enhanced CT (CECT) for diagnosing moderate-to-severe hepatic steatosis (HS), using histology as reference standard.
Classification of skeletal discrepancies by machine learning based on three-dimensional facial scans.
International journal of oral and maxillofacial surgery
Mar 17, 2025
The aim of this study was to use machine learning (ML) to classify sagittal and vertical skeletal discrepancies in three-dimensional (3D) facial scans, as well as to evaluate shape variability. 3D facial scans from 435 pre-orthodontic patients were s...
Preoperative Assessment of Ki-67 Labeling Index in Pituitary Adenomas Using Delta-Radiomics Based on Dynamic Contrast-Enhanced MRI.
Journal of magnetic resonance imaging : JMRI
Mar 17, 2025
BACKGROUND: Ki-67 labeling index (Ki-67 LI) is a proliferation marker that is correlated with aggressive behavior and prognosis of pituitary adenomas (PAs). Dynamic contrast-enhanced MRI (DCE-MRI) may potentially contribute to the preoperative assess...
Continuous real-time detection and management of comprehensive mental states using wireless soft multifunctional bioelectronics.
Biosensors & bioelectronics
Mar 17, 2025
Quantitatively measuring human mental states that profoundly affect cognition, behavior, and recovery would revolutionize personalized digital healthcare. Detecting fatigue, stress, and sleep is particularly important due to their interdependence: pe...
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