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Artifial Intelligence in the Paediatric Urology Theatre

Description 
The intraoperative period is a data-rich environment that is currently poorly captured by didactic operation reports. Intra-operative events have substantial impacts on recovery, postoperative complications and ultimate outcomes. Despite this minimal data are currently recorded, analyzed or collected in this setting. Hypospadias represents a highly variable phenotype, with a spectrum of surgical techniques for treatment. Further to specific techniques there is "devil in the detail" of how these techniques are performed on a case-be-case basis. Furthermore, even amongst world leading and experienced units hypospadias surgery retains a challenging and variable complication profile. These factors produce a fertile-ground for future studies. This project involves establishing and utilising captured surgical videos of consecutive patients and the integrated use of AI and surgical supervision to analysis operative techniques and ultimate outcomes. The systematic and methodological analysis of surgical techniques in hypospadias has great potential to deepen understanding of the cause of complications and success. This represents a significant tool in education, audit, quality improvement, and establishing an evidence-base with a greater richness then has currently been realised.
Essential criteria: 
Minimum entry requirements can be found here: https://www.monash.edu/admissions/entry-requirements/minimum
Keywords 
AI, surgery
School 
School of Clinical Sciences at Monash Health / Hudson Institute of Medical Research » Paediatrics
Available options 
PhD/Doctorate
Masters by research
BMedSc(Hons)
Time commitment 
Full-time
Physical location 
Monash Children's Hospital

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