Automated Support of Robotic Surgical Training, Operations, and Outcomes

Award Information
Agency:
Department of Defense
Branch
Army
Amount:
$99,913.00
Award Year:
2011
Program:
STTR
Phase:
Phase I
Contract:
W81XWH-11-C-0010
Award Id:
n/a
Agency Tracking Number:
A10A-029-0031
Solicitation Year:
2010
Solicitation Topic Code:
A10A-T029
Solicitation Number:
2010.A
Small Business Information
1533 Magnolia Way West, Seattle, WA, 98199-8102
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
828052568
Principal Investigator:
Thomas Lendvay
Assistant Professor, Pediatric Urol
(206) 987-1461
thomas.lendvay@seattlechildrens.org
Business Contact:
Aylin Kim
CEO'
(602) 373-3708
aylin.kim@mdbymd.com
Research Institution:
University of Washington
Lynne Chronister
Director, Office of Sponsored
4333 Brooklyn Ave., N.E
Seattle, WA, 98105-
(206) 543-4043
Nonprofit college or university
Abstract
Background: Surgical error reduction requires addressing rapid adoption of new surgical technology. We propose development of a networked surgical assessment platform able to collect performance and outcomes data from multiple surgical platforms and sites for dynamic metrics analysis. Goal: Provide surgical signature ("Surgome") of each surgeon by delivering automated performance feedback to accelerate learning curves and deriving summative and statistically valid trends in data for comparative effectiveness of new technologies. Task 1: Algorithm Development Deliverables: 1) Documentation and implementation to mathematically define metrics for rating evaluation algorithms. 2) Validation of machine learning algorithm (Autoregressive Dynamic Bayesian Network) within framework. 3) Prototype software applying this algorithm to existing surgical performance datasets. Task 2:Server Design and Implementation Deliverables: 1) On-line server running open-source operating system and database engine for storing performance data. 2) Importing and generation of full metadata for three datasets. 3) Preliminary dynamic metrics analysis software able to compute performance scores from new surgical performance data sets.

* information listed above is at the time of submission.

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