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Adaptive interventions (AIs) are increasingly becoming popular in medical and behavioral sciences. An AI is a sequence of individualized intervention options that specify for whom and under what conditions different intervention options…

Applications · Statistics 2018-12-18 Palash Ghosh , Inbal Nahum-Shani , Bonnie Spring , Bibhas Chakraborty

To optimize mobile health interventions and advance domain knowledge on intervention design, it is critical to understand how the intervention effect varies over time and with contextual information. This study aims to assess how a push…

Applications · Statistics 2024-10-22 Jiaxin Yu , Tianchen Qian

Dynamic treatment regimes (DTRs) are sequences of decision rules that recommend treatments based on patients' time-varying clinical conditions. The sequential multiple assignment randomized trial (SMART) is an experimental design that can…

Methodology · Statistics 2024-05-14 Xinru Wang , Nina Deliu , Yusuke Narita , Bibhas Chakraborty

Reliable brain tumor segmentation in MRI is indispensable for treatment planning and outcome monitoring, yet models trained on curated benchmarks often fail under domain shifts arising from scanner and protocol variability as well as…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Yuanhan Wang , Yifei Chen , Shuo Jiang , Wenjing Yu , Mingxuan Liu , Beining Wu , Jinying Zong , Feiwei Qin , Changmiao Wang , Qiyuan Tian

Randomized Controlled Trials (RCTs) are the gold standard for evaluating the effect of new medical treatments. Treatments must pass stringent regulatory conditions in order to be approved for widespread use, yet even after the regulatory…

Machine Learning · Statistics 2025-03-13 Omer Noy Klein , Alihan Hüyük , Ron Shamir , Uri Shalit , Mihaela van der Schaar

Cognitive Behavioral Therapy (CBT) is a well-established intervention for mitigating psychological issues by modifying maladaptive cognitive and behavioral patterns. However, delivery of CBT is often constrained by resource limitations and…

Artificial Intelligence · Computer Science 2024-07-30 Meng Jiang , Qing Zhao , Jianqiang Li , Fan Wang , Tianyu He , Xinyan Cheng , Bing Xiang Yang , Grace W. K. Ho , Guanghui Fu

Random testing (RT) is a well-studied testing method that has been widely applied to the testing of many applications, including embedded software systems, SQL database systems, and Android applications. Adaptive random testing (ART) aims…

Software Engineering · Computer Science 2020-07-15 Rubing Huang , Weifeng Sun , Yinyin Xu , Haibo Chen , Dave Towey , Xin Xia

Response-adaptive randomisation (RAR) can considerably improve the chances of a successful treatment outcome for patients in a clinical trial by skewing the allocation probability towards better performing treatments as data accumulates.…

Applications · Statistics 2017-03-14 Sofia S. Villar , Jack Bowden , James Wason

Randomized Controlled Trials (RCTs) are the gold standard for comparing the effectiveness of a new treatment to the current one (the control). Most RCTs allocate the patients to the treatment group and the control group by uniform…

Machine Learning · Statistics 2018-10-22 Onur Atan , William R. Zame , Mihaela van der Schaar

Clinicians and researchers alike are increasingly interested in how best to personalize interventions. A dynamic treatment regimen (DTR) is a sequence of pre-specified decision rules which can be used to guide the delivery of a sequence of…

Biomarker-guided designs are increasingly used to evaluate personalized treatments based on patients' biomarker status in Phase II and III clinical trials. With adaptive enrichment, these designs can improve the efficiency of evaluating the…

Methodology · Statistics 2024-06-11 Kaiyuan Hua , Hwanhee Hong , Xiaofei Wang

The treatment assignment mechanism in a randomized clinical trial can be optimized for statistical efficiency within a specified class of randomization mechanisms. Optimal designs of this type have been characterized in terms of the…

Methodology · Statistics 2025-09-03 Wei Zhang , Zhiwei Zhang , Aiyi Liu

This paper proposes Bayesian Adaptive Trials (BAT) as both an efficient method to conduct trials and a unifying framework for evaluation social policy interventions, addressing limitations inherent in traditional methods such as Randomized…

Randomized control trials (RCTs) have been the gold standard to evaluate the effectiveness of a program, policy, or treatment on an outcome of interest. However, many RCTs assume that study participants are willing to share their…

Applications · Statistics 2021-12-07 Manjusha Kancharla , Hyunseung Kang

Iterating between a router and a traffic micro-simulation is an increasibly accepted method for doing traffic assignment. This paper, after pointing out that the analytical theory of simulation-based assignment to-date is insufficient for…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Kai Nagel , Marcus Rickert , Patrice M. Simon , Martin Pieck

Technological advancements in the field of mobile devices and wearable sensors have helped overcome obstacles in the delivery of care, making it possible to deliver behavioral treatments anytime and anywhere. Increasingly the delivery of…

Applications · Statistics 2017-11-13 Walter Dempsey , Peng Liao , Santosh Kumar , Susan A. Murphy

Clinical trials are an instrument for making informed decisions based on evidence from well-designed experiments. Here we consider adaptive designs mainly from the perspective of multi-arm Phase II clinical trials, in which one or more…

Methodology · Statistics 2021-08-31 Elja Arjas , Dario Gasbarra

Reaction time (RT) is a fundamental measure in cognitive and neurophysiological assessment, yet most existing RT systems require active user engagement and controlled environments, limiting their use in real-world settings. This paper…

Quantitative Methods · Quantitative Biology 2026-03-13 Abhigyan Sarkar , Boris Rubinsky

Adaptive designs are increasingly used in clinical trials and online experiments to improve participant outcomes by dynamically updating treatment allocation as data accumulate. In practice, experimenters often consider multiple candidate…

Methodology · Statistics 2026-04-08 Wenxin Zhang , Aaron Hudson , Maya Petersen , Mark van der Laan

MRI-guided radiation therapy (MRgRT) offers a precise and adaptive approach to treatment planning. Deep learning applications which augment the capabilities of MRgRT are systematically reviewed. MRI-guided radiation therapy offers a…

Medical Physics · Physics 2023-03-31 Zach Eidex , Yifu Ding , Jing Wang , Elham Abouei , Richard L. J. Qiu , Tian Liu , Tonghe Wang , Xiaofeng Yang