Time-dependent prediction model using modified DeepSurv algorithm for dynamic risk assessment of post-operative bone metastases in breast cancer.

The project includes test cases and complexity analysis to validate the effectiveness of the algorithms. Among the three, Algorithm 3 is the most efficient in terms of both time and space complexity.

Given that the proposed D-SCUC model is inherently a Mixed Integer Programming (MIP) problem, the conventional branch-and-bound method incurs significant computational time and memory overhead, with ...

Adaptive Data Optimization (ADO): A New Algorithm for Dynamic Data Distribution in Machine Learning, Reducing Complexity and Improving Model Accuracy ...

Wim P. M. Vijverberg, Discrete Choices in Continuous Time as a Dynamic Programming Problem, The American Economist, Vol. 28, No. 2 (Fall, 1984), pp. 9-17 ...

Combined with the difference-based decomposed slope update method to train the PLF slopes with empirical knowledge, the proposed PLFC-ADP algorithm can handle the increasing computation complexity of ...