Proper Scoring Loss Functions Are Simple and Effective for Uncertainty Quantification of White Matter Hyperintensities

Ben Philps; Maria del c. Valdes hernandez; Miguel Bernabeu llinares

doi:10.1007/978-3-031-44336-7_21

Proper Scoring Loss Functions Are Simple and Effective for Uncertainty Quantification of White Matter Hyperintensities

Ben Philps^*, Maria del c. Valdes hernandez, Miguel Bernabeu llinares

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Original language	English
Title of host publication	International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging
Publisher	Springer
Pages	208-218
DOIs	https://doi.org/10.1007/978-3-031-44336-7_21
Publication status	Published - 7 Oct 2023

Publication series

Name	Uncertainty for Safe Utilization of Machine Learning in Medical Imaging
Volume	14291
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

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10.1007/978-3-031-44336-7_21

Calibrated_Dice_for_useful_Uncertainty_Maps (1)Accepted author manuscript, 407 KBLicence: Creative Commons: Attribution (CC-BY)

https://link.springer.com/10.1007/978-3-031-44336-7_21

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Philps, B., Valdes hernandez, M. D. C., & Bernabeu llinares, M. (2023). Proper Scoring Loss Functions Are Simple and Effective for Uncertainty Quantification of White Matter Hyperintensities. In International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging (pp. 208-218). Article Chapter 21 (Uncertainty for Safe Utilization of Machine Learning in Medical Imaging; Vol. 14291). Springer. https://doi.org/10.1007/978-3-031-44336-7_21

Philps, Ben ; Valdes hernandez, Maria del c. ; Bernabeu llinares, Miguel. / Proper Scoring Loss Functions Are Simple and Effective for Uncertainty Quantification of White Matter Hyperintensities. International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging. Springer, 2023. pp. 208-218 (Uncertainty for Safe Utilization of Machine Learning in Medical Imaging).

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title = "Proper Scoring Loss Functions Are Simple and Effective for Uncertainty Quantification of White Matter Hyperintensities",

author = "Ben Philps and {Valdes hernandez}, {Maria del c.} and {Bernabeu llinares}, Miguel",

year = "2023",

month = oct,

day = "7",

doi = "10.1007/978-3-031-44336-7_21",

language = "English",

series = "Uncertainty for Safe Utilization of Machine Learning in Medical Imaging",

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Philps, B, Valdes hernandez, MDC & Bernabeu llinares, M 2023, Proper Scoring Loss Functions Are Simple and Effective for Uncertainty Quantification of White Matter Hyperintensities. in International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging., Chapter 21, Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, vol. 14291, Springer, pp. 208-218. https://doi.org/10.1007/978-3-031-44336-7_21

Proper Scoring Loss Functions Are Simple and Effective for Uncertainty Quantification of White Matter Hyperintensities. / Philps, Ben; Valdes hernandez, Maria del c.; Bernabeu llinares, Miguel.
International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging. Springer, 2023. p. 208-218 Chapter 21 (Uncertainty for Safe Utilization of Machine Learning in Medical Imaging; Vol. 14291).

Research output: Chapter in Book/Report/Conference proceeding › Chapter

TY - CHAP

T1 - Proper Scoring Loss Functions Are Simple and Effective for Uncertainty Quantification of White Matter Hyperintensities

AU - Philps, Ben

AU - Valdes hernandez, Maria del c.

AU - Bernabeu llinares, Miguel

PY - 2023/10/7

Y1 - 2023/10/7

U2 - 10.1007/978-3-031-44336-7_21

DO - 10.1007/978-3-031-44336-7_21

M3 - Chapter

T3 - Uncertainty for Safe Utilization of Machine Learning in Medical Imaging

SP - 208

EP - 218

BT - International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging

PB - Springer

ER -

Philps B, Valdes hernandez MDC , Bernabeu llinares M. Proper Scoring Loss Functions Are Simple and Effective for Uncertainty Quantification of White Matter Hyperintensities. In International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging. Springer. 2023. p. 208-218. Chapter 21. (Uncertainty for Safe Utilization of Machine Learning in Medical Imaging). doi: 10.1007/978-3-031-44336-7_21

Proper Scoring Loss Functions Are Simple and Effective for Uncertainty Quantification of White Matter Hyperintensities

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