Suraj Rajendran

dblp:305/5215 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2026
0000-0002-8149-0157ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Medical and health informatics · 100%
Computer graphics and multimedia
1 paper
Visualization and visual analytics · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Medical and health informatics › drug development › clinical trial
clinical trial design
1.012026
TrialCompass: Visual Analytics for Enhancing the Eligibility Criteria Design of Clinical Trials · IEEE Trans. Vis. Comput. Graph. 2026
Visualization and visual analytics › visual analytics
visual analytics for healthcare
1.012026
TrialCompass: Visual Analytics for Enhancing the Eligibility Criteria Design of Clinical Trials · IEEE Trans. Vis. Comput. Graph. 2026

Methods — techniques the papers use, named apart from their topics

outcome-driven exploration · 2.0knowledge-driven exploration · 2.0history tracking · 2.0
YearPublicationVenuePosition
2026 TrialCompass: Visual Analytics for Enhancing the Eligibility Criteria Design of Clinical Trials
abstract
Eligibility criteria play a critical role in clinical trials by determining the target patient population, which significantly influences the outcomes of medical interventions. However, current approaches for designing eligibility criteria have limitations to support interactive exploration of the large space of eligibility criteria. They also ignore incorporating detailed characteristics from the original electronic health record (EHR) data for criteria refinement. To address these limitations, we proposed TrialCompass, a visual analytics system integrating a novel workflow, which can empower clinicians to iteratively explore the vast space of eligibility criteria through knowledge-driven and outcome-driven approaches. TrialCompass supports history-tracking to help clinicians trace the evolution of their adjustments and decisions when exploring various forms of data (i.e., eligibility criteria, outcome metrics, and detailed characteristics of original EHR data) through these two approaches. This feature can help clinicians comprehend the impact of eligibility criteria on outcome metrics and patient characteristics, which facilitates systematic refinement of eligibility criteria. Using a real-world dataset, we demonstrated the effectiveness of TrialCompass in providing insights into designing eligibility criteria for septic shock and sepsis-associated acute kidney injury. We also discussed the research prospects of applying visual analytics to clinical trials.
Rui Sheng, Xingbo Wang 0001, Jiachen Wang 0001, Xiaofu Jin, Zhonghua Sheng, Suraj Rajendran, Huamin Qu, Fei Wang 0001
IEEE Trans. Vis. Comput. Graph.7