Designing Support to help Health Communication Professionals Convey Numbers Clearly to the Public - A Needs Assessment and Formative Usability Evaluation
AMIA Annu Symp Proc. 2024 Jan 11;2023:1277-1286. eCollection 2023.ABSTRACTCommunicating health-related probabilities to patients and the public presents challenges, although multiple studies have demonstrated that we can promote comprehension and appropriate application of numbers by matching presentation formats (e.g., percentage, bar charts, icon arrays) to communication goal (e.g., improving recall, decreasing worry, taking action). We used this literature to create goal-driven, evidence-based guidance to support health communicators in conveying probabilities. We then conducted semi-structured interviews with 39 health...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Uday Suresh Jessica S Ancker Brian J Zikmund-Fisher Natalie C Benda Source Type: research

Standardizing Multi-site Clinical Note Titles to LOINC Document Ontology: A Transformer-based Approach
In this study we evaluated the utility of LOINC DO by mapping clinical note titles collected from five institutions to the LOINC DO and classifying the mapping into three classes based on semantic similarity between note titles and LOINC DO codes. Additionally, we developed a standardization pipeline that automatically maps clinical note titles from multiple sites to suitable LOINC DO codes, without accessing the content of clinical notes. The pipeline can be initialized with different large language models, and we compared the performances between them. The results showed that our automated pipeline achieved an accuracy o...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Xu Zuo Yujia Zhou Jon Duke George Hripcsak Nigam Shah Juan M Banda Ruth Reeves Timothy Miller Lemuel R Waitman Karthik Natarajan Hua Xu Source Type: research

Effects of Porting Essie Tokenization and Normalization to Solr
AMIA Annu Symp Proc. 2024 Jan 11;2023:369-378. eCollection 2023.ABSTRACTSearch for information is now an integral part of healthcare. Searches are enabled by search engines whose objective is to efficiently retrieve the relevant information for the user query. When it comes to retrieving biomedical text and literature, Essie search engine developed at the National Library of Medicine (NLM) performs exceptionally well. However, Essie is a software system developed for NLM that has ceased development and support. On the other hand, Solr is a popular opensource enterprise search engine used by many of the world's largest inte...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Soumya Gayen Deepak Gupta Russell F Loane Nicholas C Ide Dina Demner-Fushman Source Type: research

Towards a Machine Learning Empowered Prognostic Model for Predicting Disease Progression for Amyotrophic Lateral Sclerosis
AMIA Annu Symp Proc. 2024 Jan 11;2023:718-725. eCollection 2023.ABSTRACTAmyotrophic lateral sclerosis (ALS) is a rare and devastating neurodegenerative disorder that is highly heterogeneous and invariably fatal. Due to the unpredictable nature of its progression, accurate tools and algorithms are needed to predict disease progression and improve patient care. To address this need, we developed and compared an extensive set of screener-learner machine learning models to accurately predict the ALS Function-Rating-Scale (ALSFRS) score reduction between 3 and 12 months, by paring 5 state-of-arts feature selection algorithms wi...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Hamza Turabieh Askar S Afshar Jeffery Statland Xing Song Pooled Resource Open-Access ALS Clinical Trials Consortium* Source Type: research

De-identifying Norwegian Clinical Text using Resources from Swedish and Danish
AMIA Annu Symp Proc. 2024 Jan 11;2023:456-464. eCollection 2023.ABSTRACTThe lack of relevant annotated datasets represents one key limitation in the application of Natural Language Processing techniques in a broad number of tasks, among them Protected Health Information (PHI) identification in Norwegian clinical text. In this work, the possibility of exploiting resources from Swedish, a very closely related language, to Norwegian is explored. The Swedish dataset is annotated with PHI information. Different processing and text augmentation techniques are evaluated, along with their impact in the final performance of the mod...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Anastasios Lamproudis Sara Mora Therese Olsen Svenning Torbj ørn Torsvik Taridzo Chomutare Phuong Dinh Ngo Hercules Dalianis Source Type: research

Backdoor Adjustment of Confounding by Provenance for Robust Text Classification of Multi-institutional Clinical Notes
AMIA Annu Symp Proc. 2024 Jan 11;2023:923-932. eCollection 2023.ABSTRACTNatural Language Processing (NLP) methods have been broadly applied to clinical tasks. Machine learning and deep learning approaches have been used to improve the performance of clinical NLP. However, these approaches require sufficiently large datasets for training, and trained models have been shown to transfer poorly across sites. These issues have led to the promotion of data collection and integration across different institutions for accurate and portable models. However, this can introduce a form of bias called confounding by provenance. When so...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Xiruo Ding Zhecheng Sheng Meliha Yeti şgen Serguei Pakhomov Trevor Cohen Source Type: research

Semantically oriented EHR navigation with a patient specific knowledge base and a clinical context ontology
We report the process to create a CCO, which guides annotation of structured and narrative patient data to produce a PSKB. We also present an application of our PSKB using real patient data displayed on a semantically oriented patient summary to improve EHR navigation. Our approach can potentially save precious time spent by clinicians using today's EHRs, by showing a chronological view of the patient's record along with contextual statements needed for care decisions with minimum effort. We propose several other applications of a PSKB to improve multiple EHR functions to guide future research.PMID:38222434 | PMC:PMC107859...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Tiago K Colicchio John D Osborne Clementino V Do Rosario Ankit Anand Nicholas A Timkovich Matthew C Wyatt James J Cimino Source Type: research

Evaluation of Discrepancies Among National Library of Medicine (NLM) Value Set Authority Center (VSAC) ICD-10-CM Value Sets: Case Study for Diagnoses of Common Chronic Conditions, Implications, and Potential Solutions
AMIA Annu Symp Proc. 2024 Jan 11;2023:1087-1095. eCollection 2023.ABSTRACTThe National Library of Medicine (NLM)'s Value Set Authority Center (VSAC) is a crowd-sourced repository with a potential for substantial discrepancy among value sets for the same clinical concepts. To characterize this potential problem, we identified the most common chronic conditions affecting US adults and assessed for discrepancy among VSAC ICD-10-CM value sets for these conditions. An analysis of 32 value sets for 12 conditions identified that a median of 45% of codes for a given condition were potentially problematic (included in at least one,...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Nikolay Lukyanchikov Kensaku Kawamoto Source Type: research

Towards Understanding the Generalization of Medical Text-to-SQL Models and Datasets
AMIA Annu Symp Proc. 2024 Jan 11;2023:669-678. eCollection 2023.ABSTRACTElectronic medical records (EMRs) are stored in relational databases. It can be challenging to access the required information if the user is unfamiliar with the database schema or general database fundamentals. Hence, researchers have explored text-to-SQL generation methods that provide healthcare professionals direct access to EMR data without needing a database expert. However, currently available datasets have been essentially "solved" with state-of-the-art models achieving accuracy greater than or near 90%. In this paper, we show that there is sti...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Richard Tarbell Kim-Kwang Raymond Choo Glenn Dietrich Anthony Rios Source Type: research

Unsupervised SoftOtsuNet Augmentation for Clinical Dermatology Image Classifiers
AMIA Annu Symp Proc. 2024 Jan 11;2023:329-338. eCollection 2023.ABSTRACTData Augmentation is a crucial tool in the Machine Learning (ML) toolbox because it can extract novel, useful training images from an existing dataset, thereby improving accuracy and reducing overfitting in a Deep Neural Network (DNNs). However, clinical dermatology images often contain irrelevant background information,such as furniture and objects in the frame. DNNs make use of that information when optimizing the loss function. Data augmentation methods that preserve this information risk creating biases in the DNN's understanding (for example, that...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Miguel Dominguez John T Finnell Source Type: research

Probabilistic Prediction of Laboratory Test Information Yield
In this study, we assess whether stability in repeated laboratory diagnostic measurements is predictable with uncertainty estimates using electronic health record data available before the diagnostic is ordered. We use probabilistic regression to predict a distribution of plausible values, allowing use-time customization for various definitions of "stability" given dynamic ranges and clinical scenarios. After converting distributions into "stability" scores, the models achieve a sensitivity of 29% for white blood cells, 60% for hemoglobin, 100% for platelets, 54% for potassium, 99% for albumin and 35% for creatinine for pr...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Yixing Jiang Andrew H Lee Xiaoyuan Ni Conor K Corbin Jeremy A Irvin Andrew Y Ng Jonathan H Chen Source Type: research

Leveraging Unlabeled Clinical Data to Boost Performance of Risk Stratification Models for Suspected Acute Coronary Syndrome
AMIA Annu Symp Proc. 2024 Jan 11;2023:744-753. eCollection 2023.ABSTRACTThe performance of deep learning models in the health domain is desperately limited by the scarcity of labeled data, especially for specific clinical-domain tasks. Conversely, there are vastly available clinical unlabeled data waiting to be exploited to improve deep learning models where their training labeled data are limited. This paper investigates the use of task-specific unlabeled data to boost the performance of classification models for the risk stratification of suspected acute coronary syndrome. By leveraging large numbers of unlabeled clinica...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Yutong Wu David Conlan Siegfried Perez Anthony Nguyen Source Type: research

Digital Solutions Observed in Clinical Trials: A Formative Feasibility Scoping Review
AMIA Annu Symp Proc. 2024 Jan 11;2023:987-996. eCollection 2023.ABSTRACTGrowing digital access accelerates digital transformation of clinical trials where digital solutions (DSs) are increasingly and widely leveraged for improving trial efficiency, effectiveness, and accessibility. Many factors impact DS success including technology barriers, privacy concerns, or user engagement activities. It is unclear how those factors are considered or reported in the literature. Here, we perform a formative feasibility scoping review to identify gaps impacting DS quality and reproducibility in trials. Articles containing digital terms...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Taylor M Harrison Sungrim Moon Liwei Wang Sunyang Fu Hongfang Liu Source Type: research

Bridging the Skills Gap: Evaluating an AI-Assisted Provider Platform to Support Care Providers with Empathetic Delivery of Protocolized Therapy
AMIA Annu Symp Proc. 2024 Jan 11;2023:436-445. eCollection 2023.ABSTRACTDespite the high prevalence and burden of mental health conditions, there is a global shortage of mental health providers. Artificial Intelligence (AI) methods have been proposed as a way to address this shortage, by supporting providers with less extensive training as they deliver care. To this end, we developed the AI-Assisted Provider Platform (A2P2), a text-based virtual therapy interface that includes a response suggestion feature, which supports providers in delivering protocolized therapies empathetically. We studied providers with and without e...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: William R Kearns Jessica Bertram Myra Divina Lauren Kemp Yinzhou Wang Alex Marin Trevor Cohen Weichao Yuwen Source Type: research

Assessing Telemedicine Competencies: Developing and Validating Learner Measures for Simulation-Based Telemedicine Training
AMIA Annu Symp Proc. 2024 Jan 11;2023:474-483. eCollection 2023.ABSTRACTIn 2021, the Association of American Medical Colleges published Telehealth Competencies Across the Learning Continuum, a roadmap for designing telemedicine curricula and evaluating learners. While this document advances educators' shared understanding of telemedicine's core content and performance expectations, it does not include turn-key-ready evaluation instruments. At the University of Oklahoma School of Community Medicine, we developed a year-long telemedicine curriculum for third-year medical and second-year physician assistant students. We used ...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Blake Lesselroth Helen Monkman Ryan Palmer Craig Kuziemsky Andrew Liew Kristin Foulks Deirdra Kelly Ainsly Wolfinbarger Frances Wen Liz Kollaja Shannon Ijams Juell Homco Source Type: research