Title | ||
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Challenges associated with introduction of real-time quality monitoring and feedback during colonoscopy within a secure, tightly regulated healthcare network. |
Abstract | ||
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Colorectal cancer is a preventable disease if precursor lesions, polyps, are removed with colonoscopy. Yet, regular colonoscopy has not led to the expected decrease in mortality due to colorectal cancer; the likely reason for this is insufficiently high quality of colonoscopy. We have created novel software that performs real-time analysis of video streams for quality features during colonoscopy. The software also provides real-time feedback intended to drive the endoscopist towards high quality; in essence our software encourages continuous learning during colonoscopy on live patients. Introduction of this software at Mayo Clinic, an institution with a secure, tightly regulated network, required us to overcome an unexpected large number of challenges. Here we describe the challenges we encountered and the solutions we implemented. Of all challenges, security and network issues were most difficult to detect and resolve. |
Year | DOI | Venue |
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2014 | 10.3233/978-1-61499-405-3-592 | Frontiers in Artificial Intelligence and Applications |
Keywords | DocType | Volume |
video stream analysis,real-time feedback,colonoscopy,colorectal cancer,healthcare network,education | Conference | 262 |
ISSN | Citations | PageRank |
0922-6389 | 0 | 0.34 |
References | Authors | |
0 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Piet C. De Groen | 1 | 372 | 29.89 |
Wallapak Tavanapong | 2 | 535 | 63.27 |
JungHwan Oh | 3 | 520 | 44.87 |
Johnny Wong | 4 | 500 | 49.19 |