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OPG-based dental age estimation using a data-technical exploration of deep learning techniques.
Journal of forensic sciences
Jan 30, 2024
Dental age estimation, a cornerstone in forensic age assessment, has been extensively tried and tested, yet manual methods are impeded by tedium and interobserver variability. Automated approaches using deep transfer learning encounter challenges lik...
Multi-omics analysis identifies potential microbial and metabolite diagnostic biomarkers of bacterial vaginosis.
Journal of the European Academy of Dermatology and Venereology : JEADV
Jan 29, 2024
BACKGROUND: Bacterial vaginosis (BV) is a common clinical manifestation of a perturbed vaginal ecology associated with adverse sexual and reproductive health outcomes if left untreated. The existing diagnostic modalities are either cumbersome or requ...
Efficacy of stereotactic body radiotherapy and response prediction using artificial intelligence in oligometastatic gynaecologic cancer.
Gynecologic oncology
Jan 24, 2024
PURPOSE: We present a large real-world multicentric dataset of ovarian, uterine and cervical oligometastatic lesions treated with SBRT exploring efficacy and clinical outcomes. In addition, an exploratory machine learning analysis was performed.
Decoding Single and Paired Phonemes Using 7T Functional MRI.
Brain topography
Jan 23, 2024
Several studies have shown that mouth movements related to the pronunciation of individual phonemes are represented in the sensorimotor cortex. This would theoretically allow for brain computer interfaces that are capable of decoding continuous speec...
Three-dimensional heavily T2-weighted FLAIR in the detection of blood-labyrinthine barrier leakage in patients with sudden sensorineural hearing loss: comparison with T1 sequences and application of deep learning-based reconstruction.
European radiology
Jan 17, 2024
OBJECTIVE: Blood-labyrinthine barrier leakage has been reported in sudden sensorineural hearing loss (SSNHL). We compared immediate post-contrast 3D heavily T2-weighted fluid-attenuated inversion recovery (FLAIR), T1 spin echo (SE), and 3D T1 gradien...
Noninvasive Isocitrate Dehydrogenase 1 Status Prediction in Grade II/III Glioma Based on Magnetic Resonance Images: A Transfer Learning Strategy.
Journal of computer assisted tomography
Jan 16, 2024
OBJECTIVE: The aim of this study was to evaluate transfer learning combined with various convolutional neural networks (TL-CNNs) in predicting isocitrate dehydrogenase 1 ( IDH1 ) status of grade II/III gliomas.
Surfing the OCEAN: The machine learning psycholexical approach 2.0 to detect personality traits in texts.
Journal of personality
Jan 13, 2024
OBJECTIVE: We aimed to develop a machine learning model to infer OCEAN traits from text.
Factors Affecting Workers' Mental Stress in Handover Activities During Human-Robot Collaboration.
Human factors
Jan 12, 2024
OBJECTIVE: This study investigated the effects of different approach directions, movement speeds, and trajectories of a co-robot's end-effector on workers' mental stress during handover tasks.
A Convolutional Neural Network Model for Distinguishing Hemangioblastomas From Other Cerebellar-and-Brainstem Tumors Using Contrast-Enhanced MRI.
Journal of magnetic resonance imaging : JMRI
Jan 11, 2024
BACKGROUND: Hemangioblastoma (HB) is a highly vascularized tumor most commonly occurring in the posterior cranial fossa, requiring accurate preoperative diagnosis to avoid accidental intraoperative hemorrhage and even death.
Morphology-based molecular classification of spinal cord ependymomas using deep neural networks.
Brain pathology (Zurich, Switzerland)
Jan 11, 2024
Based on DNA-methylation, ependymomas growing in the spinal cord comprise two major molecular types termed spinal (SP-EPN) and myxopapillary ependymomas (MPE(-A/B)), which differ with respect to their clinical features and prognosis. Due to the exist...
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