AIMC Topic: Female

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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...
Pattern Recognition, Automated Movement Survivors Stroke Rehabilitation Aged Discriminant Analysis Adult Humans Electromyography Machine Learning Middle Aged Biomechanical Phenomena Stroke Algorithms Wearable Electronic Devices Male Female Feasibility Studies Muscle, Skeletal Arm Robotics
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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...
Auditory Perception Neuronal Plasticity Acoustic Stimulation Female Humans Visual Prosthesis Young Adult Visual Perception Artificial Intelligence Adult Information Theory Machine Learning Male Algorithms Learning
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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...
Aged Young Adult Adult Male Middle Aged Humans Algorithms Female Child Infant Deep Learning Radiography Adolescent Turkey Child, Preschool Age Determination by Skeleton Hand Bones
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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...
Humans Algorithms Aged, 80 and over Adult Male Middle Aged Deep Learning Retrospective Studies Tomography, X-Ray Computed Female Aged Radiographic Image Interpretation, Computer-Assisted Signal-To-Noise Ratio Radiography, Abdominal Radiography, Dual-Energy Scanned Projection
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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.
Radiographic Image Enhancement Sensitivity and Specificity Male Humans Middle Aged Deep Learning Retrospective Studies Severity of Illness Index Tomography, X-Ray Computed Fatty Liver Contrast Media Female Liver Adult Radiographic Image Interpretation, Computer-Assisted
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Artificial intelligence-based incisive canal visualization for preventing and detecting post-implant injury, using cone beam computed tomography.

International journal of oral and maxillofacial surgery Mar 17, 2025
The aim of this study was to clinically validate an artificial intelligence (AI)-based tool for automatic segmentation of the mandibular incisive canal (MIC) on cone beam computed tomography (CBCT), enabling prevention and detection of iatrogenic imp...
Male Middle Aged Cone-Beam Computed Tomography Humans Trigeminal Nerve Injuries Artificial Intelligence Imaging, Three-Dimensional Female Aged Aged, 80 and over Dental Implantation, Endosseous
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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...
Principal Component Analysis Anatomic Landmarks Cephalometry Face Malocclusion Adult Male Adolescent Imaging, Three-Dimensional Humans Machine Learning Female
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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...
Adenoma Preoperative Care Ki-67 Antigen ROC Curve Contrast Media Magnetic Resonance Imaging Pituitary Neoplasms Humans Retrospective Studies Female Reproducibility of Results Aged Adult Radiomics Male Middle Aged
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Dynamic glucose enhanced imaging using direct water saturation.

Magnetic resonance in medicine Mar 17, 2025
PURPOSE: Dynamic glucose enhanced (DGE) MRI studies employ CEST or spin lock (CESL) to study glucose uptake. Currently, these methods are hampered by low effect size and sensitivity to motion. To overcome this, we propose to utilize exchange-based li...
Humans Algorithms Brain Female Adult Brain Neoplasms Male Water Image Processing, Computer-Assisted Magnetic Resonance Imaging Glucose Gray Matter White Matter
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ECP-GAN: Generating Endometrial Cancer Pathology Images and Segmentation Labels via Two-Stage Generative Adversarial Networks.

Annals of surgical oncology Mar 17, 2025
BACKGROUND: Endometrial cancer is one of the most common tumors of the female reproductive system and ranks third in the world list of gynecological malignancies that cause death. However, due to the privacy and complexity of pathology images, it is ...
Female Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Endometrial Neoplasms Generative Adversarial Networks Humans Neural Networks, Computer Algorithms
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