AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science最新文献_第4页

ChatGPT and Vaccine Hesitancy: A Comparison of English, Spanish, and French Responses Using a Validated Scale. ChatGPT 和疫苗犹豫不决：使用经过验证的量表比较英语、西班牙语和法语的反应。

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science Pub Date : 2024-05-31 eCollection Date: 2024-01-01

Saubhagya Joshi, Eunbin Ha, Yonaira Rivera, Vivek K Singh

{"title":"ChatGPT and Vaccine Hesitancy: A Comparison of English, Spanish, and French Responses Using a Validated Scale.","authors":"Saubhagya Joshi, Eunbin Ha, Yonaira Rivera, Vivek K Singh","doi":"","DOIUrl":"","url":null,"abstract":"ChatGPT is a popular information system (over 1 billion visits in August 2023) that can generate natural language responses to user queries. It is important to study the quality and equity of its responses on health-related topics, such as vaccination, as they may influence public health decision-making. We use the Vaccine Hesitancy Scale (VHS) proposed by Shapiro et al.1 to measure the hesitancy of ChatGPT responses in English, Spanish, and French. We find that: (a) ChatGPT responses indicate less hesitancy than those reported for human respondents in past literature; (b) ChatGPT responses vary significantly across languages, with English responses being the most hesitant on average and Spanish being the least; (c) ChatGPT responses are largely consistent across different model parameters but show some variations across the scale factors (vaccine competency, risk). Results have implications for researchers interested in evaluating and improving the quality and equity of health-related web information.","PeriodicalId":72181,"journal":{"name":"AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science","volume":"2024 ","pages":"266-275"},"PeriodicalIF":0.0,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11141820/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141201520","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 Roadmap for Improving Telemedicine Support Operations. 改进远程医疗支持业务的路线图。

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science Pub Date : 2024-05-31 eCollection Date: 2024-01-01

Andrew R Ahn, Emmanuel Edu, Christina J O'Malley, Laura Kavanaugh, Alex Leiser, Linh Palcher, Christopher Erickson, Marissa Marchese, C William Hanson

引用次数: 0

Comparison of Prompt Engineering and Fine-Tuning Strategies in Large Language Models in the Classification of Clinical Notes. 比较临床笔记分类中大型语言模型的提示工程和微调策略

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science Pub Date : 2024-05-31 eCollection Date: 2024-01-01

Xiaodan Zhang, Nabasmita Talukdar, Sandeep Vemulapalli, Sumyeong Ahn, Jiankun Wang, Han Meng, Sardar Mehtab Bin Murtaza, Dmitry Leshchiner, Aakash Ajay Dave, Dimitri F Joseph, Martin Witteveen-Lane, Dave Chesla, Jiayu Zhou, Bin Chen

{"title":"Comparison of Prompt Engineering and Fine-Tuning Strategies in Large Language Models in the Classification of Clinical Notes.","authors":"Xiaodan Zhang, Nabasmita Talukdar, Sandeep Vemulapalli, Sumyeong Ahn, Jiankun Wang, Han Meng, Sardar Mehtab Bin Murtaza, Dmitry Leshchiner, Aakash Ajay Dave, Dimitri F Joseph, Martin Witteveen-Lane, Dave Chesla, Jiayu Zhou, Bin Chen","doi":"","DOIUrl":"","url":null,"abstract":"The emerging large language models (LLMs) are actively evaluated in various fields including healthcare. Most studies have focused on established benchmarks and standard parameters; however, the variation and impact of prompt engineering and fine-tuning strategies have not been fully explored. This study benchmarks GPT-3.5 Turbo, GPT-4, and Llama-7B against BERT models and medical fellows' annotations in identifying patients with metastatic cancer from discharge summaries. Results revealed that clear, concise prompts incorporating reasoning steps significantly enhanced performance. GPT-4 exhibited superior performance among all models. Notably, one-shot learning and fine-tuning provided no incremental benefit. The model's accuracy sustained even when keywords for metastatic cancer were removed or when half of the input tokens were randomly discarded. These findings underscore GPT-4's potential to substitute specialized models, such as PubMedBERT, through strategic prompt engineering, and suggest opportunities to improve open-source models, which are better suited to use in clinical settings.","PeriodicalId":72181,"journal":{"name":"AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science","volume":"2024 ","pages":"478-487"},"PeriodicalIF":0.0,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11141826/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141199710","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

Compulsory Indications in Hospital Prescribing Software Tested with Antibacterial Prescriptions. 用抗菌处方测试医院处方软件中的强制适应症。

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science Pub Date : 2024-05-31 eCollection Date: 2024-01-01

Lorna Pairman, Paul Chin, Sharon J Gardiner, Matthew Doogue

{"title":"Compulsory Indications in Hospital Prescribing Software Tested with Antibacterial Prescriptions.","authors":"Lorna Pairman, Paul Chin, Sharon J Gardiner, Matthew Doogue","doi":"","DOIUrl":"","url":null,"abstract":"The aim was to assess how making the indication field compulsory in our electronic prescribing system influenced free text documentation and to visualise prescriber behaviour. The indication field was made compulsory for seven antibacterial medicines. Text recorded in the indication field was manually classified as 'indication present', 'other text', 'rubbish text', or 'blank'. The proportion of prescriptions with an indication was compared for four weeks before and after the intervention. Indication provision increased from 10.6% to 72.4% (p<0.01) post-intervention. 'Other text' increased from 7.6% to 25.1% (p<0.01), and 'rubbish text' from 0.0% to 0.6% (p<0.01). Introducing the compulsory indication field increased indication documentation substantially with only a small increase in 'rubbish text'. An interactive report was developed using a live data extract to illustrate indication provision for all medicines prescribed at our tertiary hospital. The interactive report was validated and locally published to support audit and quality improvement projects.","PeriodicalId":72181,"journal":{"name":"AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science","volume":"2024 ","pages":"632-641"},"PeriodicalIF":0.0,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11141823/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141200027","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

Assessing the Barriers and Facilitators to Pulmonary Rehabilitation Referrals Using the Consolidated Framework for Implementation Research (CFIR). 使用实施研究综合框架 (CFIR) 评估肺康复转诊的障碍和促进因素。

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science Pub Date : 2024-05-31 eCollection Date: 2024-01-01

Aileen S Gabriel, Joseph Finkelstein

{"title":"Assessing the Barriers and Facilitators to Pulmonary Rehabilitation Referrals Using the Consolidated Framework for Implementation Research (CFIR).","authors":"Aileen S Gabriel, Joseph Finkelstein","doi":"","DOIUrl":"","url":null,"abstract":"Chronic obstructive pulmonary disease (COPD) is a global health issue causing significant illness and death. Pulmonary Rehabilitation (PR) offers non-pharmacological treatment, including education, exercise, and psychological support which was shown to improve clinical outcomes. In both stable COPD and after an acute exacerbation, PR has been demonstrated to increase exercise capacity, decrease dyspnea, and enhance quality of life. Despite these benefits, referrals for PR for COPD treatment remain low. This study aims to evaluate the perceptions of healthcare providers for referring a COPD patient to PR. Semi-structured qualitative interviews were conducted with pulmonary specialists, hospitalists, and emergency department physicians. Domains and constructs from the Consolidated Framework for Implementation Research (CFIR) were applied to the qualitative data to organize, analyze, and identify the barriers and facilitators to referring COPD patients. The findings from this study will help guide strategies to improve the referral process for PR.","PeriodicalId":72181,"journal":{"name":"AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science","volume":"2024 ","pages":"172-181"},"PeriodicalIF":0.0,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11141829/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141201475","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

Cluster Analysis of Cortical Amyloid Burden for Identifying Imaging-driven Subtypes in Mild Cognitive Impairment. 对皮质淀粉样蛋白负荷进行聚类分析以识别轻度认知障碍的成像驱动亚型

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science Pub Date : 2024-05-31 eCollection Date: 2024-01-01

Ruiming Wu, Bing He, Bojian Hou, Andrew J Saykin, Jingwen Yan, Li Shen

{"title":"Cluster Analysis of Cortical Amyloid Burden for Identifying Imaging-driven Subtypes in Mild Cognitive Impairment.","authors":"Ruiming Wu, Bing He, Bojian Hou, Andrew J Saykin, Jingwen Yan, Li Shen","doi":"","DOIUrl":"","url":null,"abstract":"Over the past decade, Alzheimer's disease (AD) has become increasingly severe and gained greater attention. Mild Cognitive Impairment (MCI) serves as an important prodromal stage of AD, highlighting the urgency of early diagnosis for timely treatment and control of the condition. Identifying the subtypes of MCI patients exhibits importance for dissecting the heterogeneity of this complex disorder and facilitating more effective target discovery and therapeutic development. Conventional method uses clinical measurements such as cognitive score and neurophysical assessment to stratify MCI patients into two groups with early MCI (EMCI) and late MCI (LMCI), which shows their progressive stages. However, such clinical method is not designed to de-convolute the heterogeneity of the disorder. This study uses a data-driven approach to divide MCI patients into a novel grouping of two subtypes based on an amyloid dataset of 68 cortical features from positron emission tomography (PET), where each subtype has a homogeneous cortical amyloid burden pattern. Experimental evaluation including visual two-dimensional cluster distribution, Kaplan-Meier plot, genetic association studies, and biomarker distribution analysis demonstrates that the identified subtypes performs better across all metrics than the conventional EMCI and LMCI grouping.","PeriodicalId":72181,"journal":{"name":"AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science","volume":"2024 ","pages":"439-448"},"PeriodicalIF":0.0,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11141862/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141199047","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

VisualSphere: a Web-based Interactive Visualization System for Clinical Research Data. VisualSphere：基于网络的临床研究数据交互式可视化系统。

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science Pub Date : 2024-05-31 eCollection Date: 2024-01-01

Shiwei Lin, Shiqiang Tao, Wei-Chun Chou, Guo-Qiang Zhang, Xiaojin Li

{"title":"VisualSphere: a Web-based Interactive Visualization System for Clinical Research Data.","authors":"Shiwei Lin, Shiqiang Tao, Wei-Chun Chou, Guo-Qiang Zhang, Xiaojin Li","doi":"","DOIUrl":"","url":null,"abstract":"Clinical research data visualization is integral to making sense of biomedical research and healthcare data. The complexity and diversity of data, along with the need for solid programming skills, can hinder advances in clinical research data visualization. To overcome these challenges, we introduce VisualSphere, a web-based interactive visualization system that directly interfaces with clinical research data repositories, streamlining and simplifying the visualization workflow. VisualSphere is founded on three primary component modules: Connection, Configuration, and Visualization. An end-user can set up connections to the data repositories, create charts by selecting the desired tables and variables, and render visualization dashboards generated by Plotly and R/Shiny. We performed a preliminary evaluation of VisualSphere, which achieved high user satisfaction. VisualSphere has the potential to serve as a versatile tool for various clinical research data repositories, enabling researchers to explore and interact with clinical research data efficiently and effectively.","PeriodicalId":72181,"journal":{"name":"AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science","volume":"2024 ","pages":"603-612"},"PeriodicalIF":0.0,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11141841/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141201310","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 Comparison of Google and ChatGPT for Automatic Generation of Health-related Multiple-choice Questions. 谷歌和 ChatGPT 在自动生成健康相关多选题方面的比较。

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science Pub Date : 2024-05-31 eCollection Date: 2024-01-01

Vivien Song, David Kauchak, John Hamre, Nick Morgenstein, Gondy Leroy

引用次数: 0

FHIRing up OpenMRS: Architecture, Implementation and Real-World Use-Cases in Global Health. FHIR up OpenMRS：全球健康领域的架构、实施和实际应用案例。

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science Pub Date : 2024-05-31 eCollection Date: 2024-01-01

I Bacher, M Goodrich, A Kimaina, M Seaton, G Faulkenberry, S Vaish, J Flowers, H S Fraser

引用次数: 0

Comparison of Three Deep Learning Models in Accurate Classification of 770 Dermoscopy Skin Lesion Images. 比较三种深度学习模型对 770 张皮肤镜皮肤病变图像的准确分类。

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science Pub Date : 2024-05-31 eCollection Date: 2024-01-01

Abdulmateen Adebiyi, Praveen Rao, Jesse Hirner, Anya Anokhin, Emily Hoffman Smith, Eduardo J Simoes, Mirna Becevic

{"title":"Comparison of Three Deep Learning Models in Accurate Classification of 770 Dermoscopy Skin Lesion Images.","authors":"Abdulmateen Adebiyi, Praveen Rao, Jesse Hirner, Anya Anokhin, Emily Hoffman Smith, Eduardo J Simoes, Mirna Becevic","doi":"","DOIUrl":"","url":null,"abstract":"Accurately determining and classifying different types of skin cancers is critical for early diagnosis. In this work, we propose a novel use of deep learning for classification of benign and malignant skin lesions using dermoscopy images. We obtained 770 de-identified dermoscopy images from the University of Missouri (MU) Healthcare. We created three unique image datasets that contained the original images and images obtained after applying a hair removal algorithm. We trained three popular deep learning models, namely, ResNet50, DenseNet121, and Inception-V3. We evaluated the accuracy and the area under the curve (AUC) receiver operating characteristic (ROC) for each model and dataset. DenseNet121 achieved the best accuracy (80.52%) and AUC ROC score (0.81) on the third dataset. For this dataset, the sensitivity and specificity were 0.80 and 0.81, respectively. We also present the SHAP (SHapley Additive exPlanations) values for the predictions made by different models to understand their interpretability.","PeriodicalId":72181,"journal":{"name":"AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science","volume":"2024 ","pages":"46-53"},"PeriodicalIF":0.0,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11141796/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141199974","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