Novel deep learning models utilising domain adaptation outperform conventional statistical models for predicting the risk of liver-related complications in patients with metabolic dysfunction-associated steatotic liver disease

Terry Cheuk-Fung Yip; Jingwen Xu; Mandy Sze-Man Lai; Sherlot Juan Song; Yee-Kit Tse; Henry L. Y. Chan; Grace Lai-Hung Wong; Pong Chi Yuen; Vincent Wai-Sun Wong

doi:10.1016/S0168-8278(24)01543-5

Novel deep learning models utilising domain adaptation outperform conventional statistical models for predicting the risk of liver-related complications in patients with metabolic dysfunction-associated steatotic liver disease

Terry Cheuk-Fung Yip
, Jingwen Xu
, Mandy Sze-Man Lai
, Sherlot Juan Song
, Yee-Kit Tse
, Henry L. Y. Chan
, Grace Lai-Hung Wong
, Pong Chi Yuen
, Vincent Wai-Sun Wong

Department of Computer Science

Research output: Contribution to journal › Conference article › peer-review

Original language	English
Pages (from-to)	S510
Number of pages	1
Journal	Journal of Hepatology
Volume	80
Issue number	Supplement 1
DOIs	https://doi.org/10.1016/S0168-8278(24)01543-5
Publication status	Published - Jun 2024
Event	European Association for the Study of the Liver Congress, EASL 2024 - Milan, Italy Duration: 5 Jun 2024 → 8 Jun 2024 https://www.sciencedirect.com/journal/journal-of-hepatology/vol/80/suppl/S1 (Conference abstract) https://www.journal-of-hepatology.eu/issue/S0168-8278(24)X0005-7 (Conference abstract)

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10.1016/S0168-8278(24)01543-5

Cite this

Yip, T. C.-F., Xu, J., Lai, M. S.-M., Song, S. J., Tse, Y.-K., Chan, H. L. Y., Wong, G. L.-H., Yuen, P. C., & Wong, V. W.-S. (2024). Novel deep learning models utilising domain adaptation outperform conventional statistical models for predicting the risk of liver-related complications in patients with metabolic dysfunction-associated steatotic liver disease. Journal of Hepatology, 80(Supplement 1), S510. https://doi.org/10.1016/S0168-8278(24)01543-5

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title = "Novel deep learning models utilising domain adaptation outperform conventional statistical models for predicting the risk of liver-related complications in patients with metabolic dysfunction-associated steatotic liver disease",

author = "Yip, \{Terry Cheuk-Fung\} and Jingwen Xu and Lai, \{Mandy Sze-Man\} and Song, \{Sherlot Juan\} and Yee-Kit Tse and Chan, \{Henry L. Y.\} and Wong, \{Grace Lai-Hung\} and Yuen, \{Pong Chi\} and Wong, \{Vincent Wai-Sun\}",

year = "2024",

month = jun,

doi = "10.1016/S0168-8278(24)01543-5",

language = "English",

volume = "80",

pages = "S510",

journal = "Journal of Hepatology",

issn = "0168-8278",

publisher = "Elsevier B.V.",

number = "Supplement 1",

note = "European Association for the Study of the Liver Congress, EASL 2024 ; Conference date: 05-06-2024 Through 08-06-2024",

url = "https://www.sciencedirect.com/journal/journal-of-hepatology/vol/80/suppl/S1, https://www.journal-of-hepatology.eu/issue/S0168-8278(24)X0005-7",

}

Yip, TC-F, Xu, J, Lai, MS-M, Song, SJ, Tse, Y-K, Chan, HLY, Wong, GL-H, Yuen, PC & Wong, VW-S 2024, 'Novel deep learning models utilising domain adaptation outperform conventional statistical models for predicting the risk of liver-related complications in patients with metabolic dysfunction-associated steatotic liver disease', Journal of Hepatology, vol. 80, no. Supplement 1, pp. S510. https://doi.org/10.1016/S0168-8278(24)01543-5

Novel deep learning models utilising domain adaptation outperform conventional statistical models for predicting the risk of liver-related complications in patients with metabolic dysfunction-associated steatotic liver disease. / Yip, Terry Cheuk-Fung; Xu, Jingwen; Lai, Mandy Sze-Man et al.
In: Journal of Hepatology, Vol. 80, No. Supplement 1, 06.2024, p. S510.

Research output: Contribution to journal › Conference article › peer-review

TY - JOUR

T1 - Novel deep learning models utilising domain adaptation outperform conventional statistical models for predicting the risk of liver-related complications in patients with metabolic dysfunction-associated steatotic liver disease

AU - Yip, Terry Cheuk-Fung

AU - Xu, Jingwen

AU - Lai, Mandy Sze-Man

AU - Song, Sherlot Juan

AU - Tse, Yee-Kit

AU - Chan, Henry L. Y.

AU - Wong, Grace Lai-Hung

AU - Yuen, Pong Chi

AU - Wong, Vincent Wai-Sun

PY - 2024/6

Y1 - 2024/6

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DO - 10.1016/S0168-8278(24)01543-5

M3 - Conference article

SN - 0168-8278

VL - 80

SP - S510

JO - Journal of Hepatology

JF - Journal of Hepatology

IS - Supplement 1

T2 - European Association for the Study of the Liver Congress, EASL 2024

Y2 - 5 June 2024 through 8 June 2024

ER -

Yip TCF, Xu J, Lai MSM, Song SJ, Tse YK, Chan HLY et al. Novel deep learning models utilising domain adaptation outperform conventional statistical models for predicting the risk of liver-related complications in patients with metabolic dysfunction-associated steatotic liver disease. Journal of Hepatology. 2024 Jun;80(Supplement 1):S510. doi: 10.1016/S0168-8278(24)01543-5

Novel deep learning models utilising domain adaptation outperform conventional statistical models for predicting the risk of liver-related complications in patients with metabolic dysfunction-associated steatotic liver disease

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