AIMC Topic: Humans

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Why do humans have unique auditory event-related fields? Evidence from computational modeling and MEG experiments.

Psychophysiology
Auditory event-related fields (ERFs) measured with magnetoencephalography (MEG) are useful for studying the neuronal underpinnings of auditory cognition in human cortex. They have a highly subject-specific morphology, albeit certain characteristic de...

Robotic MLC-based plans: A study of plan complexity.

Medical physics
PURPOSE: The utility of complexity metrics has been assessed for IMRT and VMAT treatment plans, but this analysis has never been performed for CyberKnife (CK) plans. The purpose of this study is to perform a complexity analysis of CK MLC plans, adapt...

See Like an Expert: Gaze-Augmented Training Enhances Skill Acquisition in a Virtual Reality Robotic Suturing Task.

Journal of endourology
The da Vinci Skills Simulator (DVSS) is an effective platform for robotic skills training. Novel training methods using expert gaze patterns to guide trainees have demonstrated superiority to traditional instruction. Portable head-mounted eye-tracke...

An Automated Deep Learning Method for Tile AO/OTA Pelvic Fracture Severity Grading from Trauma whole-Body CT.

Journal of digital imaging
Admission trauma whole-body CT is routinely employed as a first-line diagnostic tool for characterizing pelvic fracture severity. Tile AO/OTA grade based on the presence or absence of rotational and translational instability corresponds with need for...

Design and Implementation of Fast Spoken Foul Language Recognition with Different End-to-End Deep Neural Network Architectures.

Sensors (Basel, Switzerland)
Given the excessive foul language identified in audio and video files and the detrimental consequences to an individual's character and behaviour, content censorship is crucial to filter profanities from young viewers with higher exposure to uncensor...

A combined convolutional and recurrent neural network for enhanced glaucoma detection.

Scientific reports
Glaucoma, a leading cause of blindness, is a multifaceted disease with several patho-physiological features manifesting in single fundus images (e.g., optic nerve cupping) as well as fundus videos (e.g., vascular pulsatility index). Current convoluti...

Repeatability and reproducibility study of radiomic features on a phantom and human cohort.

Scientific reports
The repeatability and reproducibility of radiomic features extracted from CT scans need to be investigated to evaluate the temporal stability of imaging features with respect to a controlled scenario (test-retest), as well as their dependence on acqu...

Deep learning based prediction of extraction difficulty for mandibular third molars.

Scientific reports
This paper proposes a convolutional neural network (CNN)-based deep learning model for predicting the difficulty of extracting a mandibular third molar using a panoramic radiographic image. The applied dataset includes a total of 1053 mandibular thir...

Deep learning predicts postsurgical recurrence of hepatocellular carcinoma from digital histopathologic images.

Scientific reports
Recurrence risk stratification of patients undergoing primary surgical resection for hepatocellular carcinoma (HCC) is an area of active investigation, and several staging systems have been proposed to optimize treatment strategies. However, as many ...

Ranking of a wide multidomain set of predictor variables of children obesity by machine learning variable importance techniques.

Scientific reports
The increased prevalence of childhood obesity is expected to translate in the near future into a concomitant soaring of multiple cardio-metabolic diseases. Obesity has a complex, multifactorial etiology, that includes multiple and multidomain potenti...