Experiences and Perceptions of Distinct Telehealth Delivery Models for Remote Patient Monitoring among Older Adults in the Community
AMIA Annu Symp Proc. 2024 Jan 11;2023:794-803. eCollection 2023.ABSTRACTThree major telehealth delivery models-home-based, community-based, and telephone-based-have been adopted to enable remote patient monitoring of older adults to improve patient experience and reduce healthcare costs. Even though prior work has evaluated each of these delivery models, we know less about the perceptions and user experiences across these telehealth delivery models for older adults. In the present work, we addressed this research gap by interviewing 16 older adults who had experience using all these telehealth delivery models. We found tha...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Zhan Zhang Jina Huh-Yoo Karen Joy Monica Angeles David Sachs John Migliaccio Melody K Schiaffino Source Type: research
Optimizing the Synergistic Potential of Pseudo-Labels from Radiology Notes and Annotated Ground Truth in Identifying Pulmonary Opacities on Chest Radiographs for Early Detection of Acute Respiratory Distress Syndrome
AMIA Annu Symp Proc. 2024 Jan 11;2023:270-279. eCollection 2023.ABSTRACTAcute Respiratory Distress Syndrome (ARDS) is a life-threatening lung injury, hallmarks of which are bilateral radiographic opacities. Studies have shown that early recognition of ARDS could reduce severity and lethal clinical sequela. A Convolutional Neural Network (CNN) model that can identify bilateral pulmonary opacities on chest x-ray (CXR) images can aid early ARDS recognition. Obtaining large datasets with ground truth labels to train CNNs is challenging, as medical image annotation requires clinical expertise and meticulous consideration. In th...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Mehak Arora Carolyn M Davis Angana Mondal Niraj R Gowda Dennis Gene Foster Rishikesan Kamaleswaran Source Type: research
Leveraging informative missing data to learn about acute respiratory distress syndrome and mortality in long-term hospitalized COVID-19 patients throughout the years of the pandemic
AMIA Annu Symp Proc. 2024 Jan 11;2023:942-950. eCollection 2023.ABSTRACTElectronic health records (EHRs) contain a wealth of information that can be used to further precision health. One particular data element in EHRs that is not only under-utilized but oftentimes unaccounted for is missing data. However, missingness can provide valuable information about comorbidities and best practices for monitoring patients, which could save lives and reduce burden on the healthcare system. We characterize patterns of missing data in laboratory measurements collected at the University of Pennsylvania Hospital System from long-term COV...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Emily Getzen Amelia Lm Tan Gabriel Brat Gilbert S Omenn Zachary Strasser Consortium for Clinical Characterization of COVID-19 by EHR (4CE) (Collaborative Group/Consortium) Qi Long John H Holmes Danielle Mowery Source Type: research
Contextual Variation of Clinical Notes induced by EHR Migration
In this study, we evaluate the contextual variation of clinical notes by measuring the semantic and syntactic similarity of the notes of two sets of physicians comprising four medical specialties across EHR migrations at two Mayo Clinic sites. We find significant semantic and syntactic variation imposed by the context of the EHR system and between medical specialties whereas only minor variation is caused by variation of spatial context across sites. Our findings suggest that clinical language models need to account for process differences at the specialty sublanguage level to be generalizable.PMID:38222426 | PMC:PMC107858...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Kurt Miller Sungrim Moon Sunyang Fu Hongfang Liu Source Type: research
Towards Fair Patient-Trial Matching via Patient-Criterion Level Fairness Constraint
AMIA Annu Symp Proc. 2024 Jan 11;2023:884-893. eCollection 2023.ABSTRACTClinical trials are indispensable in developing new treatments, but they face obstacles in patient recruitment and retention, hindering the enrollment of necessary participants. To tackle these challenges, deep learning frameworks have been created to match patients to trials. These frameworks calculate the similarity between patients and clinical trial eligibility criteria, considering the discrepancy between inclusion and exclusion criteria. Recent studies have shown that these frameworks outperform earlier approaches. However, deep learning models m...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Chia-Yuan Chang Jiayi Yuan Sirui Ding Qiaoyu Tan Kai Zhang Xiaoqian Jiang Xia Hu Na Zou Source Type: research
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
