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ESCADA: Efficient Safety and Context Aware Dose Allocation for Precision Medicine
Ilker Demirel · Ahmet Alparslan Celik · Cem Tekin

Wed Nov 30 02:00 PM -- 04:00 PM (PST) @ Hall J #529

Finding an optimal individualized treatment regimen is considered one of the most challenging precision medicine problems. Various patient characteristics influence the response to the treatment, and hence, there is no one-size-fits-all regimen. Moreover, the administration of an unsafe dose during the treatment can have adverse effects on health. Therefore, a treatment model must ensure patient \emph{safety} while \emph{efficiently} optimizing the course of therapy. We study a prevalent medical problem where the treatment aims to keep a physiological variable in a safe range and preferably close to a target level, which we refer to as \emph{leveling}. Such a task may be relevant in numerous other domains as well. We propose ESCADA, a novel and generic multi-armed bandit (MAB) algorithm tailored for the leveling task, to make safe, personalized, and context-aware dose recommendations. We derive high probability upper bounds on its cumulative regret and safety guarantees. Following ESCADA's design, we also describe its Thompson sampling-based counterpart. We discuss why the straightforward adaptations of the classical MAB algorithms such as GP-UCB may not be a good fit for the leveling task. Finally, we make \emph{in silico} experiments on the bolus-insulin dose allocation problem in type-1 diabetes mellitus disease and compare our algorithms against the famous GP-UCB algorithm, the rule-based dose calculators, and a clinician.

Author Information

Ilker Demirel (MIT)
Ahmet Alparslan Celik (Bilkent University)
Cem Tekin (Bilkent University)

Cem is an Associate Professor in the Department of Electrical and Electronics Engineering and Head of Cognitive Systems, Bandits and Optimization Research Group (CYBORG) at Bilkent University. He received his PhD degree in Electrical Engineering: Systems from the University of Michigan, Ann Arbor, in 2013 (advisor: Mingyan Liu). He also received his MS degree in Mathematics and MSE degree in Electrical Engineering: Systems, from the University of Michigan in 2011 and 2010, respectively. Prior to attending the University of Michigan, He received his BS in Electrical and Electronics Engineering (valedictorian) from METU in 2008. From February 2013 to January 2015 he was a postdoctoral scholar in Electrical Engineering Department, UCLA (advisor: Mihaela van der Schaar). He received the Fred W. Ellersick award for the best paper in MILCOM 2009, the Science Academy Association of Turkey Distinguished Young Scientist (BAGEP) Award in 2019, Parlar Foundation Research Incentive Award in 2019, and IEEE Turkey Chapter Research Incentive Award in 2020. He is a Senior Member of IEEE. Cem has authored or coauthored over 60 research papers, 5 book chapters and a research monograph. He has served as a reviewer for numerous journals including IEEE Transactions on Information Theory, IEEE Transactions on Automatic Control, IEEE/ACM Transactions on Networking, IEEE Transactions on Signal Processing, IEEE Transactions on Image Processing, IEEE Transactions on Mobile Computing, IEEE Transactions on Wireless Communications, IEEE JSTSP and IEEE JSAC. He has served as a reviewer for NeurIPS-22, ICML-22, ICLR-22, AISTATS-22, NeurIPS-21, ICML-21, AISTATS-21, NeurIPS-20, ICML-20 and TPC member for AAAI-21, AAAI-18, ACM Mobihoc-17, AAAI-17, AAAI-16, ISM-16, ECAI-16, MLSP-15 and GlobalSIP-15.

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