AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science最新文献_第6页

Integrating a conceptual consent permission model from the informed consent ontology for software application execution. 从知情同意本体中集成概念同意许可模型，用于软件应用程序的执行。

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science Pub Date : 2025-06-10 eCollection Date: 2025-01-01

Muhammad Tuan Amith, Yongqun He, Elise Smith, Marceline Harris, Frank Manion, Cui Tao

引用次数: 0

Major Cardiovascular and Renal Complications in IgA Vasculitis: Insights from a Federated Health Research Network. IgA血管炎的主要心血管和肾脏并发症：来自联邦健康研究网络的见解。

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science Pub Date : 2025-06-10 eCollection Date: 2025-01-01

Arjun Mahajan, John Barbieri, Evan Piette

{"title":"Major Cardiovascular and Renal Complications in IgA Vasculitis: Insights from a Federated Health Research Network.","authors":"Arjun Mahajan, John Barbieri, Evan Piette","doi":"","DOIUrl":"","url":null,"abstract":"IgA Vasculitis (IgAV) is an immune-mediated condition with limited data on its long-term prognosis in adults. This study utilized the federated TriNetX network to evaluate the incidence of cardiac, renal, and vascular complications in adults diagnosed with IgAV. After propensity score matching, 12,506 patients with IgAV and 12,506 controls were analyzed. Over 6-month, 1-year, and 3-year periods, patients with IgAV had significantly higher risks of myocardial infarction, atrial fibrillation, stroke, pulmonary embolism, venous thromboembolism, chronic kidney disease, and end-stage renal disease compared to controls. Chronic kidney disease was the most common complication, with a 3-year risk of 8.6% and the highest absolute and relative risk difference. These findings suggest that adults with IgAV may be at increased risk for serious renal and cardiovascular complications, underscoring the need for further study to determine best practices for long term monitoring and management to mitigate morbidity associated with the disease.","PeriodicalId":72181,"journal":{"name":"AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science","volume":"2025 ","pages":"350-354"},"PeriodicalIF":0.0,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12150691/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144276859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DIRI: Adversarial Patient Reidentification with Large Language Models for Evaluating Clinical Text Anonymization. 使用大型语言模型评估临床文本匿名化的对抗性患者再识别。

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science Pub Date : 2025-06-10 eCollection Date: 2025-01-01

John X Morris, Thomas R Campion, Sri Laasya Nutheti, Yifan Peng, Akhil Raj, Ramin Zabih, Curtis L Cole

{"title":"DIRI: Adversarial Patient Reidentification with Large Language Models for Evaluating Clinical Text Anonymization.","authors":"John X Morris, Thomas R Campion, Sri Laasya Nutheti, Yifan Peng, Akhil Raj, Ramin Zabih, Curtis L Cole","doi":"","DOIUrl":"","url":null,"abstract":"Sharing protected health information (PHI) is critical for furthering biomedical research. Before data can be distributed, practitioners often perform deidentification to remove any PHI contained in the text. Contemporary deidentification methods are evaluated on highly saturated datasets (tools achieve near-perfect accuracy) which may not reflect the full variability or complexity of real-world clinical text and annotating them is resource intensive, which is a barrier to real-world applications. To address this gap, we developed an adversarial approach using a large language model (LLM) to re-identify the patient corresponding to a redacted clinical note and evaluated the performance with a novel De-Identification/Re-Identification (DIRI) method. Our method uses a large language model to reidentify the patient corresponding to a redacted clinical note. We demonstrate our method on medical data from Weill Cornell Medicine anonymized with three deidentification tools: rule-based Philter and two deep-learning-based models, BiLSTM-CRF and ClinicalBERT. Although ClinicalBERT was the most effective, masking all identified PII, our tool still reidentified 9% of clinical notes Our study highlights significant weaknesses in current deidentification technologies while providing a tool for iterative development and improvement.","PeriodicalId":72181,"journal":{"name":"AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science","volume":"2025 ","pages":"355-364"},"PeriodicalIF":0.0,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12150728/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144276863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Not Fully Synthetic: LLM-based Hybrid Approaches Towards Privacy-Preserving Clinical Note Sharing. 不完全合成：基于法学硕士的混合方法对隐私保护临床笔记共享。

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science Pub Date : 2025-06-10 eCollection Date: 2025-01-01

Atiquer Rahman Sarkar, Yao-Shun Chuang, Xiaoqian Jiang, Noman Mohammed

{"title":"Not Fully Synthetic: LLM-based Hybrid Approaches Towards Privacy-Preserving Clinical Note Sharing.","authors":"Atiquer Rahman Sarkar, Yao-Shun Chuang, Xiaoqian Jiang, Noman Mohammed","doi":"","DOIUrl":"","url":null,"abstract":"The publication and sharing of clinical notes are crucial for healthcare research and innovation. However, privacy regulations such as HIPAA and GDPR pose significant challenges. While de-identification techniques aim to remove protected health information, they often fall short of achieving complete privacy protection. Similarly, the current state of synthetic clinical note generation can lack nuance and content coverage. To address these limitations, we propose an approach that combines de-identification, filtration, and synthetic clinical note generation. Variations of this approach currently retain 36%-61% of the original note's content and fill the remaining gaps using an LLM, ensuring high information coverage. We also evaluated the de-identification performance of the hybrid notes, demonstrating that they surpass or at least match the standalone de-identification methods. Our results show that hybrid notes can maintain patient privacy while preserving the richness of clinical data. This approach offers a promising solution for safe and effective data sharing, encouraging further research.","PeriodicalId":72181,"journal":{"name":"AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science","volume":"2025 ","pages":"441-450"},"PeriodicalIF":0.0,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12150723/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144276876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predicting Natural Product-Drug Interactions with Knowledge Graph Embeddings. 利用知识图嵌入预测天然产物-药物相互作用。

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science Pub Date : 2025-06-10 eCollection Date: 2025-01-01

Sanya B Taneja, Israel O Dilán-Pantojas, Richard D Boyce

引用次数: 0

Reusable Generic Clinical Decision Support System Module for Immunization Recommendations in Resource-Constraint Settings. 可重复使用的通用临床决策支持系统模块的免疫建议在资源限制的设置。

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science Pub Date : 2025-06-10 eCollection Date: 2025-01-01

Samuil Orlioglu, Akash Shanmugan Boobalan, Kojo Abanyie, Richard D Boyce, Hua Min, Yang Gong, Dean F Sittig, Paul Biondich, Adam Wright, Christian Nøhr, Timothy Law, David Robinson, Arild Faxvaag, Nina Hubig, Ronald Gimbel, Lior Rennert, Xia Jing

{"title":"Reusable Generic Clinical Decision Support System Module for Immunization Recommendations in Resource-Constraint Settings.","authors":"Samuil Orlioglu, Akash Shanmugan Boobalan, Kojo Abanyie, Richard D Boyce, Hua Min, Yang Gong, Dean F Sittig, Paul Biondich, Adam Wright, Christian Nøhr, Timothy Law, David Robinson, Arild Faxvaag, Nina Hubig, Ronald Gimbel, Lior Rennert, Xia Jing","doi":"","DOIUrl":"","url":null,"abstract":"Clinical decision support systems (CDSS) are routinely employed in clinical settings to improve quality of care, ensure patient safety, and deliver consistent medical care. However, rule-based CDSS, currently available, do not feature reusable rules. In this study, we present CDSS with reusable rules. Our solution includes a common CDSS module, electronic medical record (EMR) specific adapters, CDSS rules written in the clinical quality language (CQL) (derived from CDC immunization recommendations), and patient records in fast healthcare interoperability resources (FHIR) format. The proposed CDSS is entirely browser-based and reachable within the user's EMR interface at the client-side. This helps to avoid the transmission ofpatient data and privacy breaches. Additionally, we propose to provide means of managing and maintaining CDSS rules to allow the end users to modify them independently. Successful implementation and deployment were achieved in OpenMRS and OpenEMR during initial testing.","PeriodicalId":72181,"journal":{"name":"AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science","volume":"2025 ","pages":"395-404"},"PeriodicalIF":0.0,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12150700/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144276882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SmartState: An Automated Research Protocol Adherence System. SmartState：一个自动化的研究协议遵守系统。

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science Pub Date : 2025-06-10 eCollection Date: 2025-01-01

Samuel E Armstrong, Mitchell A Klusty, Aaron D Mullen, Jeffery C Talbert, Cody Bumgardner

引用次数: 0

Utilization of an AI-Powered Chatbot for Enhancing Oral Cancer Awareness among African Americans: Expert Feedback on Usability. 利用人工智能聊天机器人提高非裔美国人对口腔癌的认识：专家对可用性的反馈。

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science Pub Date : 2025-06-10 eCollection Date: 2025-01-01

Nour Abosamak, Asmaa Namoos, Janina Golob Deeb, Tamas Gal

{"title":"Utilization of an AI-Powered Chatbot for Enhancing Oral Cancer Awareness among African Americans: Expert Feedback on Usability.","authors":"Nour Abosamak, Asmaa Namoos, Janina Golob Deeb, Tamas Gal","doi":"","DOIUrl":"","url":null,"abstract":"Oral and oropharyngeal cancers disproportionately affect Black Americans, contributing to significant healthcare disparities due to late-stage diagnoses and limited awareness. AI-powered chatbots have the potential to address these challenges by offering scalable, interactive, and personalized educational tools. This study evaluated the usability and accuracy of a Large Language Model-powered chatbot prototype under a Retrieval Augmented Generation framework designed to enhance oral cancer awareness, using a mixed-methods approach with six technical and clinical experts. Usability and accuracy were rated positively by 83.3% of the experts, with median scores of 6.65 and 7.67, respectively. Key areas for improvement included providing a clear introduction, simplifying the interface, addressing accessibility issues, and incorporating features like next-question suggestions, downloadable chats, and reference links. While content accuracy was well-received, gaps in conversational flow and technical term definitions were noted. These findings highlight the chatbot's potential to improve health literacy and reduce disparities.","PeriodicalId":72181,"journal":{"name":"AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science","volume":"2025 ","pages":"42-45"},"PeriodicalIF":0.0,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12150737/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144276906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AI Mapping of In-House Codes to LOINC Codes Using Laboratory Test Results Excluding Test Names: Toward International Sharing of Medical Data. 使用实验室测试结果（不包括测试名称）将内部代码人工智能映射为LOINC代码：实现医疗数据的国际共享。

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science Pub Date : 2025-06-10 eCollection Date: 2025-01-01

Noriyuki Shido, Yuma Iwahashi, Hidenari Ohsawa, Katsushige Furuya, Yasumichi Sakai, Masamichi Ishii, Hiroyuki Hoshimoto, Nobukazu Namiki, Kengo Miyo

引用次数: 0

Automatically Identifying Event Reports of Workplace Violence and Communication Failures using Large Language Models. 使用大型语言模型自动识别工作场所暴力和沟通失败事件报告。

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science Pub Date : 2025-06-10 eCollection Date: 2025-01-01

Mike Becker, Sy Hwang, Emily Schriver, Caryn Douma, Caoimhe Duffy, Joshua Atkins, Caitlyn McShane, Jason Lubken, Asaf Hanish, John D McGreevey, Susan Harkness Regli, Danielle L Mowery

引用次数: 0