AMIA ... Annual Symposium proceedings. AMIA Symposium最新文献_第10页

Influence of the CONCERN Early Warning System on Unanticipated ICU Transfers, In-Hospital Mortality, and Length of Stay: Results from a Multi-site Pragmatic Randomized Controlled Clinical Trial. CONCERN预警系统对意外ICU转院、住院死亡率和住院时间的影响：一项多地点实用随机对照临床试验的结果

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01

Rachel Y Lee, Kenrick D Cato, Patricia C Dykes, Graham Lowenthal, Jennifer B Withall, Sandy Cho, Haomiao Jia, Sarah C Rossetti

{"title":"Influence of the CONCERN Early Warning System on Unanticipated ICU Transfers, In-Hospital Mortality, and Length of Stay: Results from a Multi-site Pragmatic Randomized Controlled Clinical Trial.","authors":"Rachel Y Lee, Kenrick D Cato, Patricia C Dykes, Graham Lowenthal, Jennifer B Withall, Sandy Cho, Haomiao Jia, Sarah C Rossetti","doi":"","DOIUrl":"","url":null,"abstract":"Communicating Narrative Concerns Entered by RNs Early Warning System (CONCERN EWS) is a machine-learning predictive model that leverages nursing surveillance documentation patterns to predict deterioration risks for hospitalized patients. In a retrospective cohort study of 1,013 hospital encounters with unanticipated ICU transfers from a multi-site pragmatic randomized controlled trial, we assessed the influence of CONCERN EWS on in-hospital mortality and length of stay following unanticipated ICU transfers. Chi-square tests, t-tests, multivariate logistic regression, and generalized linear models were used. Our findings showed that patients who had unanticipated ICU transfers from acute care units with CONCERN EWS had a lower in-hospital mortality rate and a shorter average hospital stay than those transferred from units receiving usual care. These results suggest that CONCERN EWS enhances shared situational awareness for care teams, improves communication, and effectively facilitates timely interventions, thereby streamlining care processes and improving patient outcomes.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2024 ","pages":"655-663"},"PeriodicalIF":0.0,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12099359/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144144674","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

Ontology-based modeling, integration, and analysis of heterogeneous clinical, pathological, and molecular kidney data for precision medicine. 基于本体的建模、整合和分析异构临床、病理和分子肾数据，用于精准医学。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01

Yongqun Oliver He, Laura Barisoni, Avi Z Rosenberg, Peter Robinson, Alexander D Diehl, Yichao Chen, Jim Phuong, Jens Hansen, Bruce W Herr Ii, Katy Börner, Jennifer Schaub, Nikki Bonevich, Ghida Arnous, Saketh Boddapati, Jie Zheng, Fadhl Alakwaa, Pinaki Sardar, William D Duncan, Chen Liang, M Todd Valerius, Sanjay Jain, Ravi Iyengar, Jonathan Himmelfarb, Matthias Kretzler

{"title":"Ontology-based modeling, integration, and analysis of heterogeneous clinical, pathological, and molecular kidney data for precision medicine.","authors":"Yongqun Oliver He, Laura Barisoni, Avi Z Rosenberg, Peter Robinson, Alexander D Diehl, Yichao Chen, Jim Phuong, Jens Hansen, Bruce W Herr Ii, Katy Börner, Jennifer Schaub, Nikki Bonevich, Ghida Arnous, Saketh Boddapati, Jie Zheng, Fadhl Alakwaa, Pinaki Sardar, William D Duncan, Chen Liang, M Todd Valerius, Sanjay Jain, Ravi Iyengar, Jonathan Himmelfarb, Matthias Kretzler","doi":"","DOIUrl":"","url":null,"abstract":"Many data resources generate, process, store, or provide kidney related molecular, pathological, and clinical data. Reference ontologies offer an opportunity to support knowledge and data integration. The Kidney Precision Medicine Project (KPMP) team contributed to the representation and addition of 329 kidney phenotype terms to the Human Phenotype Ontology (HPO), and identified many subcategories of acute kidney injury (AKI) or chronic kidney disease (CKD). The Kidney Tissue Atlas Ontology (KTAO) imports and integrates kidney-related terms from existing ontologies (e.g., HPO, CL, and Uberon) and represents 259 kidney-related biomarkers. We have also developed a precision medicine metadata ontology (PMMO) to integrate 50 variables from KPMP and CZ CellxGene data resources and applied PMMO for integrative kidney data analysis. The gene expression profiles of kidney gene biomarkers were specifically analyzed under healthy control or AKI/CKD disease states. This work demonstrates how ontology-based approaches support multi-domain data and knowledge integration in precision medicine.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2024 ","pages":"523-532"},"PeriodicalIF":0.0,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12099421/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144144641","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

Where do doctors disagree? Characterizing Decision Points for Safe Reinforcement Learning in Choosing Vasopressor Treatment. 医生们在哪些方面存在分歧？选择血管加压药物治疗的安全强化学习决策点特征。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01

Esther Brown, Shivam Raval, Alex Rojas, Jiayu Yao, Sonali Parbhoo, Leo A Celi, Siddharth Swaroop, Weiwei Pan, Finale Doshi-Velez

{"title":"Where do doctors disagree? Characterizing Decision Points for Safe Reinforcement Learning in Choosing Vasopressor Treatment.","authors":"Esther Brown, Shivam Raval, Alex Rojas, Jiayu Yao, Sonali Parbhoo, Leo A Celi, Siddharth Swaroop, Weiwei Pan, Finale Doshi-Velez","doi":"","DOIUrl":"","url":null,"abstract":"In clinical settings, domain experts sometimes disagree on optimal treatment actions. These \"decision points\" must be comprehensively characterized, as they offer opportunities for Artificial Intelligence (AI) to provide statistically informed recommendations. To address this, we introduce a pipeline to investigate \"decision regions\", clusters of decision points, by training classifiers for prediction and applying clustering techniques to the classifier's embedding space. Our methodology includes: a robustness analysis confirming the topological stability of decision regions across diverse design parameters; an empirical study using the MIMIC-III database, focusing on the binary decision to administer vasopressors to hypotensive patients in the ICU; and an expert-validated summary of the decision regions' statistical attributes with novel clinical interpretations. We demonstrate that the topology of these decision regions remains stable across various design choices, reinforcing the reliability of our findings and generalizability of our approach. We encourage future work to extend this approach to other medical datasets.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2024 ","pages":"222-231"},"PeriodicalIF":0.0,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12099420/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144144360","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

Combining Rule-based NLP-lite with Rapid Iterative Chart Adjudication for Creation of a Large, Accurately Curated Cohort from EHR data: A Case Study in the Context of a Clinical Trial Emulation. 将基于规则的NLP-lite与快速迭代图表裁决相结合，从电子病历数据中创建一个大型，准确策划的队列：临床试验模拟背景下的案例研究。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01

Pradeep Mutalik, Kei-Hoi Cheung, Jennifer Green, Melissa Buelt-Gebhardt, Karen F Anderson, Vales Jeanpaul, Linda McDonald, Michael Wininger, Yuli Li, Nallakkandi Rajeevan, Peter M Jessel, Hans Moore, Selçuk Adabag, Merritt H Raitt, Mihaela Aslan

{"title":"Combining Rule-based NLP-lite with Rapid Iterative Chart Adjudication for Creation of a Large, Accurately Curated Cohort from EHR data: A Case Study in the Context of a Clinical Trial Emulation.","authors":"Pradeep Mutalik, Kei-Hoi Cheung, Jennifer Green, Melissa Buelt-Gebhardt, Karen F Anderson, Vales Jeanpaul, Linda McDonald, Michael Wininger, Yuli Li, Nallakkandi Rajeevan, Peter M Jessel, Hans Moore, Selçuk Adabag, Merritt H Raitt, Mihaela Aslan","doi":"","DOIUrl":"","url":null,"abstract":"The aim of this work was to create a gold-standard curated cohort of 10,000+ cases from the Veteran Affairs (VA) corporate data warehouse (CDW) for virtual emulation of a randomized clinical trial (CSP#592). The trial had six inclusion/exclusion criteria lacking adequate structured data. We therefore used a hybrid computer/human approach to extract information from clinical notes. Rule-based NLP output was iteratively adjudicated by a panel of trained non-clinician content experts and non-experts using an easy-to-use spreadsheet-based rapid adjudication display. This group-adjudication process iteratively sharpened both the computer algorithm and clinical decision criteria, while simultaneously training the non-experts. The cohort was successfully created with each inclusion/exclusion decision backed by a source document. Less than 0.5% of cases required referral to specialist clinicians. It is likely that such curated datasets capturing specialist reasoning and using a process-supervised approach will acquire greater importance as training tools for future clinical AI applications.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2024 ","pages":"847-856"},"PeriodicalIF":0.0,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12099393/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144144433","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

Derivation and Experimental Performance of Standard and Novel Uncertainty Calibration Techniques. 标准和新型不确定度校准技术的推导和实验性能。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01

Katherine E Brown, Steve Talbert, Douglas A Talbert

引用次数: 0

Large-scale Text Mining of Suicide Attempt improves Identification of Distinct Suicidal Events in Electronic Health Records. 自杀企图的大规模文本挖掘提高了电子健康记录中不同自杀事件的识别。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01

Hyunjoon Lee, Cosmin A Bejan, Colin G Walsh

引用次数: 0

Exploring the use of Artificial Genomes for Genome-wide Association Studies through the lens of Utility and Privacy. 通过效用和隐私的视角探索人工基因组在全基因组关联研究中的应用。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01

Xinyue Wang, Sitao Min, Jaideep Vaidya

{"title":"Exploring the use of Artificial Genomes for Genome-wide Association Studies through the lens of Utility and Privacy.","authors":"Xinyue Wang, Sitao Min, Jaideep Vaidya","doi":"","DOIUrl":"","url":null,"abstract":"Collaborative Genome-wide association studies (GWAS) have the potential to uncover rare genetic variant-trait associations by leveraging larger datasets and diverse population samples. Despite this potential, privacy concerns and cumbersome review processes for data validation and collaborator selection hinder their broader implementation. Advances in generative models present a possible solution by generating synthetic datasets that closely resemble real genomic data, thus enhancing privacy and expediting the review process. This study assesses the capability of deep generative models to produce artificial genomic data for GWAS applications. We evaluate two state-of-the-art models on real-world datasets, identifying significant limitations in their ability to generate high-quality artificial genomes. Furthermore, we demonstrate that prevailing privacy measures, mainly based on membership inference attacks, are inadequate for providing insightful privacy evaluations. Our findings highlight the critical challenges and suggest future directions for the effective use of artificial genomes in GWAS.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2024 ","pages":"1196-1205"},"PeriodicalIF":0.0,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12099349/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144144612","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

Integrated Hands-Free Electronic Patient Care Report (ePCR) Charting (IHeC): Designing the Architecture. 集成免提电子病人护理报告（ePCR）图表（IHeC）：体系结构设计。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01

Desmond R Hedderson, Claudia Lai

引用次数: 0

"Getting people access to services is also getting them access to a phone": Clarifying digital divide dynamics and their consequences in Community Mental Health Care. “让人们获得服务也让他们获得电话”：澄清社区精神卫生保健中的数字鸿沟动态及其后果。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01

Alicia K Williamson, Ella Jiaqi Li, Tiffany C Veinot

{"title":"\"Getting people access to services is also getting them access to a phone\": Clarifying digital divide dynamics and their consequences in Community Mental Health Care.","authors":"Alicia K Williamson, Ella Jiaqi Li, Tiffany C Veinot","doi":"","DOIUrl":"","url":null,"abstract":"Access to mental healthcare is increasingly technologically-mediated. People with low socioeconomic status (SES) and serious mental illness (SMI) face lower rates of tech ownership and may lack technological skills, called \"digital divides.\" Yet, little is known about how digital divides may impact mental healthcare access. Therefore, a qualitative study (ethnographic observations and interviews) was conducted with stakeholders working with low-SES SMI patients using community mental health care (CMH) (N=14). Findings showed that consumers struggled to maintain consistent internet-and thus mental healthcare-access despite owning smartphones. Consumers frequently faced care disruptions due to broken, lost, or uncharged phones. Staff and patients created effortful but ad-hoc workarounds to restore access during technological access disruptions. These solutions frequently occurred after healthcare appointments were missed. Digital divide concepts should accommodate the work necessary to maintain technology access even after ownership and its impact on care access-especially among low-SES SMI patients.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2024 ","pages":"1245-1254"},"PeriodicalIF":0.0,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12099397/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144144677","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

A Comprehensive System for Searching and Evaluating Genomic Variant Evidence Using AI and Knowledge Bases to Support Personalized Medicine. 利用人工智能和知识库搜索和评估基因组变异证据的综合系统以支持个性化医疗。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01

Jinlian Wang, Hui Li, Hongfang Liu

{"title":"A Comprehensive System for Searching and Evaluating Genomic Variant Evidence Using AI and Knowledge Bases to Support Personalized Medicine.","authors":"Jinlian Wang, Hui Li, Hongfang Liu","doi":"","DOIUrl":"","url":null,"abstract":"We introduce an innovative automated system for the search and assessment of genetic variant evidence, meticulously aligned with ACMG guidelines. Leveraging the synergistic power of artificial intelligence (AI), elastic search, and an extensive knowledge base, our system advances the efficiency and accuracy of genetic variant interpretation. Distinct from existing methodologies, it features a pioneering literature filtering mechanism that automates the identification and relevance ranking of scientific articles, significantly reducing the time spending on literature evidence search and optimizing the evidence assessment process. Implemented and rigorously tested by a commercial company hereditary cancer variant curation team, the system demonstrated its effectiveness and scalability by processing over 3 million PMIDs and 1.8 million full-text articles. Throughout the period of active utilization, significant insights were gleaned into the real-world impact and user experience of the system, conclusively affirming its robustness. Our comparative analysis with Mastermind 2.0 highlights the system's enhanced performance in minimizing false positives for various mutation types. The core AI model exhibits exceptional precision, recall, and F1 scores above 0.8, signifying its adeptness in selecting pertinent literature for variant classification. The experience and knowledge acquired from deploying the system in a commercial setting provide a distinctive outlook on its practicality and prospects for future development. The novel integration of AI with traditional genetic variant curation processes heralds a new era in the field, promising significant advancements and broader application prospects.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2024 ","pages":"1206-1214"},"PeriodicalIF":0.0,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12099401/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144144681","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