{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T20:46:54Z","timestamp":1792097214985,"version":"4.4.0"},"reference-count":11,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Med Inform"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec sec-type=\"background\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Pedigree mapping serves as the first step in genetic counseling. Traditional methods relying on manual pedigree drawing and information collection are inefficient and prone to errors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"objective\">\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aimed to design an intelligent pedigree mapping system based on a specialized model, intended to automate family history collection and standardized pedigree map generation through conversational interaction, thereby enhancing the clinical efficiency of genetic counseling.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This study adopted a participatory design and iterative development approach. We formed an interdisciplinary team comprising gynecologic oncologists, genetic counselors, AI engineers, and patient representatives. The system was built around a proprietary, specialized large language model for gynecologic oncology, featuring a microservices architecture that included pedigree data collection. Through 4 iterative cycles, we integrated specialized knowledge bases using retrieval-augmented generation technology and applied a novel graph-based kinship inference and validation module. The system\u2019s performance was comprehensively evaluated based on the accuracy of pedigree map generation and user feedback on usability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We significantly improved system performance by optimizing dialogue strategies, expanding the knowledge base, and applying self-developed algorithms to improve data extraction accuracy. The initial database of the system defined 100 core information nodes and matched approximately 800 user expression examples, while the final pilot version of the database was expanded to 245 core information nodes and 2256 user expression examples. Although the AI function was limited in the early stage, the final version of the system demonstrated outstanding accuracy in generating genealogy nodes and relationships. Test users generally gave positive reviews of the system\u2019s innovation, ease of use, and intuitiveness of information presentation, believing it to have great potential in clinical practice.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"conclusions\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The developed system is an accurate, efficient auxiliary tool, and pilot validation showed promising preliminary performance. After pilot clinical validation, it holds promise for integration into routine clinical workflows to optimize genetic counseling services.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/78080","type":"journal-article","created":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T20:23:14Z","timestamp":1792095794000},"page":"e78080-e78080","source":"Crossref","is-referenced-by-count":0,"title":["Construction of an AI-Assisted Pedigree Mapping System for Hereditary Gynecological Tumors: Algorithm Development and Pilot Validation Study"],"prefix":"10.2196","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1105-1917","authenticated-orcid":false,"given":"Jing","family":"Xu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-4310-3664","authenticated-orcid":false,"given":"Yajun","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-1312-6933","authenticated-orcid":false,"given":"Hui","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7191-0757","authenticated-orcid":false,"given":"Jiayang","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-5872-5587","authenticated-orcid":false,"given":"Xingang","family":"Lei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7954-5892","authenticated-orcid":false,"given":"Congjian","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1197-4727","authenticated-orcid":false,"given":"Yu","family":"Kang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,10,15]]},"reference":[{"issue":"14","key":"R1","doi-asserted-by":"publisher","first-page":"1278","DOI":"10.1001\/jama.2025.9495","article-title":"Ovarian cancer: a review","volume":"334","author":"Caruso","journal-title":"JAMA"},{"issue":"5","key":"R2","doi-asserted-by":"publisher","DOI":"10.3390\/cancers15051400","article-title":"Lynch syndrome and gynecologic tumors: incidence, prophylaxis, and management of patients with cancer","volume":"15","author":"Capasso","journal-title":"Cancers (Basel)"},{"issue":"2","key":"R3","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1007\/s10689-024-00373-4","article-title":"Cascade genetic testing for hereditary cancer syndromes: a review of barriers and breakthroughs","volume":"23","author":"Levine","journal-title":"Fam Cancer"},{"issue":"2","key":"R4","doi-asserted-by":"publisher","first-page":"546","DOI":"10.1002\/jgc4.1524","article-title":"Awareness of genetic counseling and genetic testing for hereditary gynecologic cancers among Korean healthcare providers: a survey","volume":"31","author":"Kim","journal-title":"J Genet Couns"},{"key":"R5","doi-asserted-by":"publisher","DOI":"10.3389\/fgene.2023.1239817","article-title":"The growing needs of genetic counselling-feasibility in utilization of tele-genetic counselling in Asia and Hong Kong","volume":"14","author":"Chu","journal-title":"Front Genet"},{"issue":"6","key":"R6","doi-asserted-by":"publisher","first-page":"1488","DOI":"10.1016\/j.pec.2021.09.027","article-title":"Ask Rosa - the making of a digital genetic conversation tool, a chatbot, about hereditary breast and ovarian cancer","volume":"105","author":"Siglen","journal-title":"Patient Educ Couns"},{"key":"R7","doi-asserted-by":"publisher","DOI":"10.1016\/j.ygyno.2024.04.006","article-title":"ChatGPT accurately performs genetic counseling for gynecologic cancers","volume":"183","author":"Patel","journal-title":"Gynecol Oncol"},{"issue":"8","key":"R8","doi-asserted-by":"publisher","first-page":"1337","DOI":"10.1038\/s43018-025-00991-6","article-title":"Development and validation of an autonomous artificial intelligence agent for clinical decision-making in oncology","volume":"6","author":"Ferber","journal-title":"Nat Cancer"},{"key":"R9","doi-asserted-by":"publisher","DOI":"10.2196\/48914","article-title":"Preliminary screening for hereditary breast and ovarian cancer using an AI chatbot as a genetic counselor: clinical study","volume":"26","author":"Sato","journal-title":"J Med Internet Res"},{"issue":"4","key":"R10","doi-asserted-by":"publisher","first-page":"481","DOI":"10.1016\/S1470-2045(19)30142-1","article-title":"Artificial intelligence, chatbots, and the future of medicine","volume":"20","author":"Greene","journal-title":"Lancet Oncol"},{"issue":"1","key":"R11","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1002\/jgc4.1192","article-title":"Artificial intelligence in genetic services delivery: utopia or apocalypse?","volume":"29","author":"Kearney","journal-title":"J Genet Couns"}],"container-title":["JMIR Medical Informatics"],"original-title":[],"language":"en","deposited":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T20:23:15Z","timestamp":1792095795000},"score":1,"resource":{"primary":{"URL":"https:\/\/medinform.jmir.org\/2026\/1\/e78080"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,15]]},"references-count":11,"URL":"https:\/\/doi.org\/10.2196\/78080","relation":{},"ISSN":["2291-9694"],"issn-type":[{"value":"2291-9694","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,15]]},"article-number":"v14i14e78080"}}