AIMC Topic: Humans

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Game-based learning as training to use a chemotherapy preparation robot.

Journal of oncology pharmacy practice : official publication of the International Society of Oncology Pharmacy Practitioners
INTRODUCTION: In 2015, our university hospital pharmacy acquired the PharmaHelp robot system to automate part of its chemotherapy production. Complex technical use, downtime periods, and insufficient training caused a drop in motivation and dispariti...

Automated permanent tooth detection and numbering on panoramic radiograph using a deep learning approach.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: This study aimed to assess the performance of the deep learning (DL) model for automated tooth numbering in panoramic radiographs.

The Feasibility, Proficiency, and Mastery Learning Curves in 635 Robotic Pancreatoduodenectomies Following a Multicenter Training Program: "Standing on the Shoulders of Giants".

Annals of surgery
OBJECTIVE: To assess the feasibility, proficiency, and mastery learning curves for robotic pancreatoduodenectomy (RPD) in "second-generation" RPD centers following a multicenter training program adhering to the IDEAL framework.

Automatic Detection of Pancreatic Lesions and Main Pancreatic Duct Dilatation on Portal Venous CT Scans Using Deep Learning.

Investigative radiology
OBJECTIVES: This study proposes and evaluates a deep learning method to detect pancreatic neoplasms and to identify main pancreatic duct (MPD) dilatation on portal venous computed tomography scans.

Deep-learning based fast and accurate 3D CT deformable image registration in lung cancer.

Medical physics
BACKGROUND: Deformable Image Registration (DIR) is an essential technique required in many applications of radiation oncology. However, conventional DIR approaches typically take several minutes to register one pair of 3D CT images and the resulting ...

Advances in Image-Based Artificial Intelligence in Otorhinolaryngology-Head and Neck Surgery: A Systematic Review.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVE: To update the literature and provide a systematic review of image-based artificial intelligence (AI) applications in otolaryngology, highlight its advances, and propose future challenges.

Deep Ensembles Are Robust to Occasional Catastrophic Failures of Individual DNNs for Organs Segmentations in CT Images.

Journal of digital imaging
Deep neural networks (DNNs) have recently showed remarkable performance in various computer vision tasks, including classification and segmentation of medical images. Deep ensembles (an aggregated prediction of multiple DNNs) were shown to improve a ...

Deep Learning for the Assessment of Facial Nerve Palsy: Opportunities and Challenges.

Facial plastic surgery : FPS
Automated evaluation of facial palsy using machine learning offers a promising solution to the limitations of current assessment methods, which can be time-consuming, labor-intensive, and subject to clinician bias. Deep learning-driven systems have t...

Performance of an automated deep learning algorithm to identify hepatic steatosis within noncontrast computed tomography scans among people with and without HIV.

Pharmacoepidemiology and drug safety
PURPOSE: Hepatic steatosis (fatty liver disease) affects 25% of the world's population, particularly people with HIV (PWH). Pharmacoepidemiologic studies to identify medications associated with steatosis have not been conducted because methods to eva...

Artificial Intelligence framework with traditional computer vision and deep learning approaches for optimal automatic segmentation of left ventricle with scar.

Artificial intelligence in medicine
Automatic segmentation of the cardiac left ventricle with scars remains a challenging and clinically significant task, as it is essential for patient diagnosis and treatment pathways. This study aimed to develop a novel framework and cost function to...