Irene Lo

All Publications

• Two-Sided Benefits of Price Transparency in Smallholder Supply Chains MANAGEMENT SCIENCE Shi, Y., de Zegher, J. F., Lo, I. Y. 2025

  View details for DOI 10.1287/mnsc.2023.01617

  View details for Web of Science ID 001585744800001

• Quickest way to less headache days: an operational research model and its implementation for chronic migraine. BMC neurology Lo, I., Zhang, P. 2025; 25 (1): 132

  Abstract

  Choosing migraine prevention medications often involves trial and error. Operations research methodologies, however, allow us to derive a mathematically optimum way to conduct such trial and error processes.Given probability of success (defined as 50% reduction in headache days) and adverse events as a function of time, we seek to develop and solve an operations research model, applicable to any arbitrary patient, minimizing time until discovery of an effective migraine prevention medication. We then seek to apply our model to real life data for chronic migraine prevention.An operations research model is developed and then solved for the optimum solution, taking into account the likelihood of reaching 50% headache day reduction as a function of time. We then estimate key variables using FORWARD study by Rothrock et al. as well as erenumab data published by Barbanti et al. at International Headache Congress 2019.The solution for our model is to order the medications in decreasing order by probability of efficacy per unit time. This result can be generalized through calculation of Gittins index. In the case of chronic migraine the optimum sequence of chronic migraine prevention medication is a trial of erenumab for 12 weeks, followed by a trial of onabotulinumtoxinA for 32 weeks, followed by a trial of topiramate for 32 weeks.We propose an optimal sequence for preventive medication trial for patients with chronic migraine. Since our model makes limited assumptions on the characteristics of disease, it can be readily applied also to episodic migraine, given the appropriate data as input. Indeed, our model can be applied to other scenarios so long as probability of success/adverse event as a function of time can be estimated. As such, we believe our model may have implications beyond our sub-specialty.

  View details for DOI 10.1186/s12883-025-04124-5

  View details for PubMedID 40165130

  View details for PubMedCentralID 3606966

• Commitment on Volunteer Crowdsourcing Platforms: Implications for Growth and Engagement M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT Lo, I., Manshadi, V., Rodilitz, S., Shameli, A. 2024

  View details for DOI 10.1287/msom.2020.0426

  View details for Web of Science ID 001198289900001

• Editors' Introduction ACM SIGECOM EXCHANGES Lo, I., Taggart, S. 2023; 21 (1): 1-2

  View details for Web of Science ID 001207037100001

• Rank-heterogeneous Preference Models for School Choice Awadelkarim, A., Seshadri, A., Ashlagi, I., Lo, I., Ugander, J., ACM ASSOC COMPUTING MACHINERY. 2023: 47-56

  View details for DOI 10.1145/3580305.3599484

  View details for Web of Science ID 001118896300005

• Editors' Introduction ACM SIGECOM EXCHANGES Lo, I., Talgam-Cohen, I. 2022; 20 (2): 1-2

  View details for Web of Science ID 000947940700001

• Editors' Introduction ACM SIGECOM EXCHANGES Lo, I., Talgam-Cohen, I. 2022; 20 (1): 1-2

  View details for Web of Science ID 000891505400001

• Optimizing strategies for post-disaster reconstruction of school systems RELIABILITY ENGINEERING & SYSTEM SAFETY Alisjahbana, I., Graur, A., Lo, I., Kiremidjian, A. 2022; 219

  View details for DOI 10.1016/j.ress.2021.108253

  View details for Web of Science ID 000760341500042

• Simple and Approximately Optimal Contracts for Payment for Ecosystem Services MANAGEMENT SCIENCE Li, W., Ashlagi, I., Lo, I. 2022

  View details for DOI 10.1287/mnsc.2021.4273

  View details for Web of Science ID 000828393000001

• Designing School Choice for Diversity in the San Francisco Unified School District Allman, M., Ashlagi, I., Lo, I., Love, J., Mentzer, K., Ruiz-Setz, L., O'Connell, H. 2022

  View details for DOI 10.1145/3490486.3538271

• Explaining a Potential Interview Match for Graduate Medical Education. Journal of graduate medical education Wapnir, I., Ashlagi, I., Roth, A. E., Skancke, E., Vohra, A., Lo, I., Melcher, M. L. 1800; 13 (6): 764-767

  View details for DOI 10.4300/JGME-D-20-01422.1

  View details for PubMedID 35070086

• Invitation to Participate in the ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO'21) SI GECOM EXCHANGES Abebe, R., Lo, I., Stoica, A. 2021; 19 (1): 10-11

  View details for Web of Science ID 000674752000003

• The Cutoff Structure of Top Trading Cycles in School Choice REVIEW OF ECONOMIC STUDIES Leshno, J. D., Lo, I. 2021; 88 (4): 1582-1623

  View details for DOI 10.1093/restud/rdaa071

  View details for Web of Science ID 000710586200002

• Decentralized Matching in a Probabilistic Environment Proceedings of the 22nd ACM Conference on Economics and Computation Jeloudar, M. Y., Lo, I., Pollner, T., Saberi, A. 2021

  View details for DOI 10.1145/3465456.3467652

• Dynamic Matching in School Choice: Efficient Seat Reassignment After Late Cancellations MANAGEMENT SCIENCE Feigenbaum, I., Kanoria, Y., Lo, I., Sethuraman, J. 2020; 66 (11): 5341–61

  View details for DOI 10.1287/mnsc.2019.3469

  View details for Web of Science ID 000587780600023

• Benefits of an interview match for breast fellowship positions Wapnir, I., Lo, I., Roth, A., Ashlagi, I., Melcher, M. SPRINGER. 2019: 279–80

  View details for Web of Science ID 000467382700224

• The extremal function for disconnected minors JOURNAL OF COMBINATORIAL THEORY SERIES B Csoka, E., Lo, I., Norin, S., Wu, H., Yepremyan, L. 2017; 126: 162-174

  View details for DOI 10.1016/j.jctb.2017.04.005

  View details for Web of Science ID 000405538500007

• Decomposing and Clique-Coloring (Diamond, Odd-Hole)-Free Graphs JOURNAL OF GRAPH THEORY Chudnovsky, M., Lo, I. 2017; 86 (1): 5-41

  View details for DOI 10.1002/jgt.22110

  View details for Web of Science ID 000405285400001