@inproceedings{d7ebd086b36f4409865a2ba484df2e6a,
title = "The AI-Medic: A Multimodal Artificial Intelligent Mentor for Trauma Surgery",
abstract = "Telementoring generalist surgeons as they treat patients can be essential when in situ expertise is not readily available. However, adverse cyber-attacks, unreliable network conditions, and remote mentors' predisposition can significantly jeopardize the remote intervention. To provide medical practitioners with guidance when mentors are unavailable, we present the AI-Medic, the initial steps towards the development of a multimodal intelligent artificial system for autonomous medical mentoring. The system uses a tablet device to acquire the view of an operating field. This imagery is provided to an encoder-decoder neural network trained to predict medical instructions from the current view of a surgery. The network was training using DAISI, a dataset including images and instructions providing step-by-step demonstrations of surgical procedures. The predicted medical instructions are conveyed to the user via visual and auditory modalities.",
keywords = "datasets, neural networks, surgery, telementoring",
author = "Edgar Rojas-Mu{\~n}oz and Kyle Couperus and Wachs, {Juan P.}",
note = "Publisher Copyright: {\textcopyright} 2020 Owner/Author.; 22nd ACM International Conference on Multimodal Interaction, ICMI 2020 ; Conference date: 25-10-2020 Through 29-10-2020",
year = "2020",
month = oct,
day = "21",
doi = "10.1145/3382507.3421167",
language = "English",
series = "ICMI 2020 - Proceedings of the 2020 International Conference on Multimodal Interaction",
publisher = "Association for Computing Machinery, Inc",
pages = "766--767",
booktitle = "ICMI 2020 - Proceedings of the 2020 International Conference on Multimodal Interaction",
}