Application of Unbalanced Optimal Transport in Healthcare

Optimal Transport (OT) is a powerful tool widely used in healthcare applications, but its high computational cost and sensitivity to data changes make it less practical for resource-constrained settings. These limitations also contribute to increased environmental impact due to higher CO2 emissions from computing. To address these challenges, we explore Unbalanced Optimal Transport (UOT), a variation of OT that is both computationally efficient and more robust to data variability. We apply UOT to two healthcare scenarios: independence testing on breast cancer data and modeling heart rate variability (HRV). Our experiments show that UOT not only reduces computational costs but also delivers reliable results, making it a practical alternative to OT for socially impactful applications.

@article{Pham2024,
  title     = {Application of Unbalanced Optimal Transport in Healthcare},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {11},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Qui Phu Pham and Nghia Thu Truong and Hoang-Hiep Nguyen-Mau and Cuong Nguyen and Mai Ngoc Tran and Dung Luong},
  doi       = {10.14569/IJACSA.2024.0151110},
  url       = {https://doi.org/10.14569/IJACSA.2024.0151110}
}