... IEEE Workshop on Visual Analytics in Healthcare. IEEE Workshop on Visual Analytics in Healthcare最新文献

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Lessons from the Development and Deployment of an Interactive Oncological Risk Estimator. 互动式肿瘤风险评估器的开发和部署的经验教训。

... IEEE Workshop on Visual Analytics in Healthcare. IEEE Workshop on Visual Analytics in Healthcare Pub Date : 2025-11-02 Epub Date: 2025-12-23 DOI: 10.1109/vahc69430.2025.00009

Nafiul Nipu, L V van Dijk, Guadalupe Canahuate, C David Fuller, G Elisabeta Marai

{"title":"Lessons from the Development and Deployment of an Interactive Oncological Risk Estimator.","authors":"Nafiul Nipu, L V van Dijk, Guadalupe Canahuate, C David Fuller, G Elisabeta Marai","doi":"10.1109/vahc69430.2025.00009","DOIUrl":"10.1109/vahc69430.2025.00009","url":null,"abstract":"In the precision medicine paradigm, oncological treatment leverages complex ensemble datasets of similar patients to estimate the outcomes for a current patient. A key challenge is developing and deploying easy-to-understand AI predictive models for the outcomes of a specific patient, based on patient data from multiple institutions. We describe the lessons learned from the development and deployment of an interactive dashboard to support the analysis of individual head and neck cancer patient outcomes based on cohort data. As required by the project, the dashboard design aims to handle a large client base. The dashboard combines an AI solution with a multi-view interface featuring domain-specific plots to facilitate the visual analysis of patient outcomes and to quickly stratify new patients into risk groups. A year after the successful public deployment of the dashboard, we evaluate it with clinician domain experts. We report the feedback and we reflect on the lessons learned through this experience.","PeriodicalId":519974,"journal":{"name":"... IEEE Workshop on Visual Analytics in Healthcare. IEEE Workshop on Visual Analytics in Healthcare","volume":"2025 ","pages":"29-35"},"PeriodicalIF":0.0,"publicationDate":"2025-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13417431/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148623615","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

The Iterative Design Process of an Explainable AI Application for Non-Invasive Diagnosis of CNS Tumors: A User-Centered Approach. 用于中枢神经系统肿瘤非侵入性诊断的可解释人工智能应用程序的迭代设计过程：以用户为中心的方法

... IEEE Workshop on Visual Analytics in Healthcare. IEEE Workshop on Visual Analytics in Healthcare Pub Date : 2023-10-01 Epub Date: 2023-12-18 DOI: 10.1109/vahc60858.2023.00008

Eric W Prince, Todd C Hankinson, Carsten Görg

{"title":"The Iterative Design Process of an Explainable AI Application for Non-Invasive Diagnosis of CNS Tumors: A User-Centered Approach.","authors":"Eric W Prince, Todd C Hankinson, Carsten Görg","doi":"10.1109/vahc60858.2023.00008","DOIUrl":"10.1109/vahc60858.2023.00008","url":null,"abstract":"Artificial Intelligence (AI) is well-suited to help support complex decision-making tasks within clinical medicine, including clinical imaging applications like radiographic differential diagnosis of central nervous system (CNS) tumors. So far, there have been numerous examples of theoretical AI solutions for this space, for example, large-scale corporate efforts like IBM's Watson AI. However, clinical implementation remains limited due to factors related to the alignment of this technology in the clinical setting. User-Centered Design (UCD) is a design philosophy that focuses on developing tailored solutions for specific users or user groups. In this study, we applied UCD to develop an explainable AI tool to support clinicians in our use case. Through four design iterations, starting from basic functionality and visualizations, we progressed to functional prototypes in a realistic testing environment. We discuss our motivation and approach for each iteration, along with key insights gained. This UCD process has advanced our conceptual idea from feasibility testing to interactive functional AI interfaces designed for specific clinical and cognitive tasks. It has also provided us with directions to develop further an AI system for the non-invasive diagnosis of CNS tumors.","PeriodicalId":519974,"journal":{"name":"... IEEE Workshop on Visual Analytics in Healthcare. IEEE Workshop on Visual Analytics in Healthcare","volume":"2023 ","pages":"7-13"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11235084/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141581954","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