{"doi":"10.1016/j.csbj.2025.12.007","title":"Developing provider digital twins for personalized provider-patient communication via a RAG-based conversational framework","abstract":"Digital twins have emerged as a paradigm in precision and personalized medicine, enabling data-driven modeling of individuals to support tailored interventions. While most existing work focuses on patient-oriented twins, little attention has been given to modeling the provider's role, particularly in clinical communication. In this study, we present GRACE (Generalized RAG-Enhanced Conversation Framework), a framework for constructing a provider digital twin (ProDT) that emulates key aspects of clinicians' communicative and cognitive behavior. GRACE integrates three modules: a physician-informed dialog script generation and optimization module for provider-patterned conversation, a Retrieval-Augmented Generation (RAG) pipeline for factual grounding and timely knowledge updating, and an LLM-based conversational interface that enables interactive, context-aware exchanges. Using HPV vaccination counseling as a representative use case, GRACE was evaluated with HealthBench and a structured user study involving clinician feedback. The results demonstrate its feasibility, trustworthiness, and adaptability for proactive provider-patient communication, marking a conceptual step toward safe, scalable, and cognitively grounded digital twins in healthcare.","journal":"Computational and Structural Biotechnology Journal","year":2025,"id":549557,"datarank":0.10397207708399181,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.0,"self_endowment_contribution":0.10397207708399181,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9546,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1444286,"name":"Yutong Hu","orcid":null,"position":1,"is_corresponding":false},{"id":576098,"name":"Jianfu Li","orcid":"0000-0002-9949-7007","position":2,"is_corresponding":false},{"id":1444287,"name":"Garit Gemeinhardt","orcid":null,"position":3,"is_corresponding":false},{"id":347168,"name":"Fang Li","orcid":"0000-0001-8865-7717","position":4,"is_corresponding":false},{"id":285085,"name":"Muhammad Amith","orcid":"0000-0003-4333-1857","position":5,"is_corresponding":false},{"id":110439,"name":"Licong Cui","orcid":"0000-0001-5549-8780","position":6,"is_corresponding":false},{"id":449230,"name":"Antonio J. Forte","orcid":"0000-0003-2004-7538","position":7,"is_corresponding":false},{"id":23317,"name":"Cui Tao","orcid":"0000-0002-4267-1924","position":8,"is_corresponding":false},{"id":1393713,"name":"Pengze Li","orcid":"0000-0001-7015-0491","position":0,"is_corresponding":true}],"reference_count":19,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T02:54:07.823422Z","pmid":"41551040","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}