Machine learning approach for analyzing mixed case interval censored data with a cured subgroup

Wisdom Aselisewine & Suvra Pal

AStA Advances in Statistical Analysis2025https://doi.org/10.1007/s10182-025-00544-3article
ABDC C
Weight
0.37

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https://doi.org/https://doi.org/10.1007/s10182-025-00544-3

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@article{wisdom2025,
  title        = {{Machine learning approach for analyzing mixed case interval censored data with a cured subgroup}},
  author       = {Wisdom Aselisewine & Suvra Pal},
  journal      = {AStA Advances in Statistical Analysis},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1007/s10182-025-00544-3},
}

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Machine learning approach for analyzing mixed case interval censored data with a cured subgroup

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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