A data-driven performance dashboard for surgical dissection
Abstract Surgical error and resulting complication have significant patient and economic consequences. Inappropriate exertion of tool-tissue force is a common variable for such error, that can be objectively monitored by sensorized tools. The rich digital output establishes a powerful skill assessme...
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Nature Portfolio
2021
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oai:doaj.org-article:48461ef9a2ad4dc6ae77c79d3ab2a2642021-12-02T17:55:13ZA data-driven performance dashboard for surgical dissection10.1038/s41598-021-94487-92045-2322https://doaj.org/article/48461ef9a2ad4dc6ae77c79d3ab2a2642021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-94487-9https://doaj.org/toc/2045-2322Abstract Surgical error and resulting complication have significant patient and economic consequences. Inappropriate exertion of tool-tissue force is a common variable for such error, that can be objectively monitored by sensorized tools. The rich digital output establishes a powerful skill assessment and sharing platform for surgical performance and training. Here we present SmartForceps data app incorporating an Expert Room environment for tracking and analysing the objective performance and surgical finesse through multiple interfaces specific for surgeons and data scientists. The app is enriched by incoming geospatial information, data distribution for engineered features, performance dashboard compared to expert surgeon, and interactive skill prediction and task recognition tools to develop artificial intelligence models. The study launches the concept of democratizing surgical data through a connectivity interface between surgeons with a broad and deep capability of geographic reach through mobile devices with highly interactive infographics and tools for performance monitoring, comparison, and improvement.Amir BaghdadiSanju LamaRahul SinghHamidreza HoshyarmaneshMohammadsaleh RazmiGarnette R. SutherlandNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021) |
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Medicine R Science Q Amir Baghdadi Sanju Lama Rahul Singh Hamidreza Hoshyarmanesh Mohammadsaleh Razmi Garnette R. Sutherland A data-driven performance dashboard for surgical dissection |
description |
Abstract Surgical error and resulting complication have significant patient and economic consequences. Inappropriate exertion of tool-tissue force is a common variable for such error, that can be objectively monitored by sensorized tools. The rich digital output establishes a powerful skill assessment and sharing platform for surgical performance and training. Here we present SmartForceps data app incorporating an Expert Room environment for tracking and analysing the objective performance and surgical finesse through multiple interfaces specific for surgeons and data scientists. The app is enriched by incoming geospatial information, data distribution for engineered features, performance dashboard compared to expert surgeon, and interactive skill prediction and task recognition tools to develop artificial intelligence models. The study launches the concept of democratizing surgical data through a connectivity interface between surgeons with a broad and deep capability of geographic reach through mobile devices with highly interactive infographics and tools for performance monitoring, comparison, and improvement. |
format |
article |
author |
Amir Baghdadi Sanju Lama Rahul Singh Hamidreza Hoshyarmanesh Mohammadsaleh Razmi Garnette R. Sutherland |
author_facet |
Amir Baghdadi Sanju Lama Rahul Singh Hamidreza Hoshyarmanesh Mohammadsaleh Razmi Garnette R. Sutherland |
author_sort |
Amir Baghdadi |
title |
A data-driven performance dashboard for surgical dissection |
title_short |
A data-driven performance dashboard for surgical dissection |
title_full |
A data-driven performance dashboard for surgical dissection |
title_fullStr |
A data-driven performance dashboard for surgical dissection |
title_full_unstemmed |
A data-driven performance dashboard for surgical dissection |
title_sort |
data-driven performance dashboard for surgical dissection |
publisher |
Nature Portfolio |
publishDate |
2021 |
url |
https://doaj.org/article/48461ef9a2ad4dc6ae77c79d3ab2a264 |
work_keys_str_mv |
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