AIMC Topic: Humans

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Dense reinforcement learning for safety validation of autonomous vehicles.

Nature
One critical bottleneck that impedes the development and deployment of autonomous vehicles is the prohibitively high economic and time costs required to validate their safety in a naturalistic driving environment, owing to the rarity of safety-critic...

Deep learning-based artificial intelligence model for classification of vertebral compression fractures: A multicenter diagnostic study.

Frontiers in endocrinology
OBJECTIVE: To develop and validate an artificial intelligence diagnostic system based on X-ray imaging data for diagnosing vertebral compression fractures (VCFs).

Robotic single-port multiquadrant surgery to treat renal tumors and benign abdominal conditions.

Minerva surgery
BACKGROUND: Multiquadrant procedures are technically more demanding than sequential operations. The new single port (SP) system allows to work in every abdominal quadrant maintaining an adequate triangulation without the need for changes in the port ...

Joint action with human and robotic co-actors: Self-other integration is immune to the perceived humanness of the interacting partner.

Quarterly journal of experimental psychology (2006)
When performing a joint action task, we automatically represent the action and/or task constraints of the co-actor with whom we are interacting. Current models suggest that, not only physical similarity, but also abstract, conceptual features shared ...

Deep learning-based high-accuracy detection for lumbar and cervical degenerative disease on T2-weighted MR images.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: To develop and validate a deep learning (DL) model for detecting lumbar degenerative disease in both sagittal and axial views of T2-weighted MRI and evaluate its generalized performance in detecting cervical degenerative disease.

XGBoost-aided prediction of lip prominence based on hard-tissue measurements and demographic characteristics in an Asian population.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics
INTRODUCTION: Prediction of lip prominence based on hard-tissue measurements could be helpful in orthodontic treatment planning and has been challenging and formidable thus far.

Application of synthetic data in the training of artificial intelligence for automated quality assurance in magnetic resonance imaging.

Medical physics
BACKGROUND: Magnetic resonance imaging scanner faults can be missed during routine quality assurance (QA) if they are subtle, intermittent, or the test being performed is insensitive to the type of fault. Coil element malfunction is a common fault wi...

Application of Deep Learning-Based Denoising Technique for Radiation Dose Reduction in Dynamic Abdominal CT: Comparison with Standard-Dose CT Using Hybrid Iterative Reconstruction Method.

Journal of digital imaging
The purpose is to evaluate whether deep learning-based denoising (DLD) algorithm provides sufficient image quality for abdominal computed tomography (CT) with a 30% reduction in radiation dose, compared to standard-dose CT reconstructed with conventi...

Comparison of deep learning-based reconstruction of PROPELLER Shoulder MRI with conventional reconstruction.

Skeletal radiology
OBJECTIVE: To compare the image quality and agreement among conventional and accelerated periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) MRI with both conventional reconstruction (CR) and deep learning-based r...