Evidence-Centered Clinical Intelligence for Drug Discovery, Trial Recruitment, and Personalized Care
Keywords:
clinical intelligence, drug discovery, trial recruitment, pharmacogenomics, medical imaging, personalized careAbstract
This paper develops an evidence-centered clinical intelligence architecture that links drug-gene reasoning, trial eligibility screening, medical imaging, and personalized care while preserving calibration and privacy. The work is motivated by a cross-domain synthesis of 156 supplied studies and is organized around a deployment question rather than a single leaderboard claim. We define a problem formulation, separate representation, adaptation, decision, and assurance layers, and specify a reproducible comparison protocol. The manuscript includes a literature evidence map, a system architecture figure, and qualitative comparison tables. Because no raw dataset or verified experimental log was provided, the tables and figures describe framework structure and evidence requirements rather than invented performance results. The proposed protocol can be instantiated on a real dataset by fixing a data contract, an evaluation split, resource constraints, and a human-review policy. The resulting design is intended to support an auditable EI-style conference submission while keeping factual claims bounded by the supplied bibliography.
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