Addressing Challenges to Enable Better Use of Routinely Collected Clinical Photographs: Evaluating the Largest Cleft Dataset for Machine Learning Analysis

C Turnbull; A Macleod; S Esposito; R Gorantla; S Seth; R Ramamoorthy; F Mehendale

doi:10.1093/bjs/znac269.310

Addressing Challenges to Enable Better Use of Routinely Collected Clinical Photographs: Evaluating the Largest Cleft Dataset for Machine Learning Analysis

C Turnbull, A Macleod, S Esposito, R Gorantla, S Seth, R Ramamoorthy, F Mehendale

Research output: Contribution to journal › Meeting abstract › peer-review

Original language	English
Number of pages	1
Journal	British Journal of Surgery
Volume	109
Issue number	SUPPL 6
DOIs	https://doi.org/10.1093/bjs/znac269.310
Publication status	Published - 19 Aug 2022
Event	46th International Surgical Conference, 2022 - Aberdeen, United Kingdom Duration: 4 Mar 2022 → 6 Mar 2022 Conference number: 46

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10.1093/bjs/znac269.310

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title = "Addressing Challenges to Enable Better Use of Routinely Collected Clinical Photographs: Evaluating the Largest Cleft Dataset for Machine Learning Analysis",

author = "C Turnbull and A Macleod and S Esposito and R Gorantla and S Seth and R Ramamoorthy and F Mehendale",

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AU - Esposito, S

AU - Gorantla, R

AU - Seth, S

AU - Ramamoorthy, R

AU - Mehendale, F

N1 - Conference code: 46

PY - 2022/8/19

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M3 - Meeting abstract

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VL - 109

JO - British Journal of Surgery

JF - British Journal of Surgery

IS - SUPPL 6

Y2 - 4 March 2022 through 6 March 2022

ER -

Addressing Challenges to Enable Better Use of Routinely Collected Clinical Photographs: Evaluating the Largest Cleft Dataset for Machine Learning Analysis

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