Dissemination of Tuberculosis Clinical Evidence - An Application of Network Analysis to Publicly Available Resources.
Authors: Abrams M, Wang D Abstract Effective dissemination of Tuberculosis (TB) clinical evidence to healthcare providers is essential to address this pandemic. To identify, organize, and aggregate online TB information resources, we analyzed the websites of four CDC-funded TB Centers of Excellence (COE), identified the hosted resources, examined the outward linkages, and collected the external resources. We obtained 154 primary resources from TB COEs and 1521 linkages to external resources. We leveraged a network analysis approach to construct resource networks at the individual resource and parent site levels. We...
Source: AMIA Annual Symposium Proceedings - July 7, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Evaluating the Portability of an NLP System for Processing Echocardiograms: A Retrospective, Multi-site Observational Study.
This study investigated the portability of an NLP system developed initially at the Department of Veterans Affairs (VA) to extract 27 key cardiac concepts from free-text or semi-structured echocardiograms from three academic edical centers: Weill Cornell Medicine, Mayo Clinic and Northwestern Medicine. While the NLP system showed high precision and recall easurements for four target concepts (aortic valve regurgitation, left atrium size at end systole, mitral valve regurgitation, tricuspid valve regurgitation) across all sites, we found moderate or poor results for the remaining concepts and the NLP system performance vari...
Source: AMIA Annual Symposium Proceedings - July 7, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Using Priorities of Hospitalized Patients and Their Caregivers to Develop Personas.
Authors: Agapie E, Kendall L, Mishra SR, Haldar S, Khelifi M, Pollack A, Pratt W Abstract Hospitalized patients and their caregivers often access technologies like patient portals to understand what happens during their hospital stay. Although this access can lead to more patient engagement and positive health outcomes, many find that the technology does not support their needs. As a first step toward improving patient-facing technologies we create personas for hospitalized patients and their caregivers by following the Q Methodology, a technique for quantifying subjective opinion. We clustered 28 hospitalized pati...
Source: AMIA Annual Symposium Proceedings - July 7, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Smartphone Monitoring of Mood Instability in Young Depressed Patients: A Latent-class Analyses.
CONCLUSION: Smartphone ratings may adequately capture mood instability in BD subjects and at risk HRMDD subjects and offers a prudent way for monitoring development of serious manic symptoms. PMID: 32308814 [PubMed - indexed for MEDLINE] (Source: AMIA Annual Symposium Proceedings)
Source: AMIA Annual Symposium Proceedings - July 7, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Towards Reliable ARDS Clinical Decision Support: ARDS Patient Analytics with Free-text and Structured EMR Data.
Authors: Apostolova E, Uppal A, Galarraga JE, Koutroulis I, Tschampel T, Wang T, Velez T Abstract In this work, we utilize a combination of free-text and structured data to build Acute Respiratory Distress Syndrome(ARDS) prediction models and ARDS phenotype clusters. We derived 'Patient Context Vectors' representing patientspecific contextual ARDS risk factors, utilizing deep-learning techniques on ICD and free-text clinical notes data. The Patient Context Vectors were combined with structured data from the first 24 hours of admission, such as vital signs and lab results, to build an ARDS patient prediction model a...
Source: AMIA Annual Symposium Proceedings - July 7, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Non-Negative Matrix Factorization for Drug Repositioning: Experiments with the repoDB Dataset.
Authors: Bakal G, Kilicoglu H, Kavuluru R Abstract Computational methods for drug repositioning are gaining mainstream attention with the availability of experimental gene expression datasets and manually curated relational information in knowledge bases. When building repurpos-ing tools, a fundamental limitation is the lack of gold standard datasets that contain realistic true negative examples of drug-disease pairs that were shown to be non-indications. To address this gap, the repoDB dataset was created in 2017 as a first of its kind realistic resource to benchmark drug repositioning methods - its positive examp...
Source: AMIA Annual Symposium Proceedings - July 7, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Feasibility Assessment of a Pre-Hospital Automated Sensing Clinical Documentation System.
Authors: Bloos SM, McNaughton CD, Coco JR, Novak LL, Adams JA, Bodenheimer RE, Ehrenfeld JM, Heard JR, Paris RA, Simpson CL, Scully DM, Fabbri D Abstract Clinical documentation in the pre-hospital setting is challenged by limited resources and fast-paced, high-acuity. Military and civilian medics are responsible for performing procedures and treatments to stabilize the patient, while transporting the injured to a trauma facility. Upon arrival, medics typically give a verbal report from memory or informal source of documentation such as a glove or piece of tape. The development of an automated documentation system w...
Source: AMIA Annual Symposium Proceedings - July 7, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

One-Way and Round-Trip Analysis Demonstrates Surprising Limitations of Standards-Based Terminology Maps.
We present an error framework, lessons learned, and proposed mitigating steps to enhance standards-based semantic interoperability. PMID: 32308818 [PubMed - indexed for MEDLINE] (Source: AMIA Annual Symposium Proceedings)
Source: AMIA Annual Symposium Proceedings - July 7, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Determination of Marital Status of Patients from Structured and Unstructured Electronic Healthcare Data.
Authors: Bucher BT, Shi J, Pettit RJ, Ferraro J, Chapman WW, Gundlapalli A Abstract Social Determinants of Health, including marital status, are becoming increasingly identified as key drivers of health care utilization. This paper describes a robust method to determine the marital status of patients using structured and unstructured electronic healthcare data from a single academic institution in the United States. We developed and validated a natural language processing pipeline (NLP) for the ascertainment of marital status from clinical notes and compared the performance against two baseline methods: a machine l...
Source: AMIA Annual Symposium Proceedings - July 7, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

2018 Salary Survey of AMIA Members: Factors Associated with Higher Salaries.
Authors: Cheng Y, Mohanty AF, Ogunyemi OI, Smith CA, Leroy G, Zeng QT Abstract Greater transparency in salaries overall and in factors associated with differing salaries can help students and professionals plan their careers, discover biases and obstacles, and help advance professional disciplines broadly. In March 2018, we conducted the first salary survey of American Medical Informatics Association members. Our goal was to summarize salary information and provide a nuanced view pertaining to the diverse biomedical informatics community. To identify factors associated with higher salaries, we reviewed average sala...
Source: AMIA Annual Symposium Proceedings - July 7, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Interpretation of machine learning predictions for patient outcomes in electronic health records.
Authors: Cava W, Bauer C, Moore JH, Pendergrass SA Abstract Electronic health records are an increasingly important resource for understanding the interactions between patient health, environment, and clinical decisions. In this paper we report an empirical study of predictive modeling of seven patient outcomes using three state-of-the-art machine learning methods. Our primary goal is to validate the models by interpreting the importance of predictors in the final models. Central to interpretation is the use of feature importance scores, which vary depending on the underlying methodology. In order to assess feature...
Source: AMIA Annual Symposium Proceedings - June 24, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Interpretation of 'Omics dynamics in a single subject using local estimates of dispersion between two transcriptomes.
Authors: Li Q, Zaim SR, Aberasturi D, Berghout J, Li H, Vitali F, Kenost C, Zhang HH, Lussier YA Abstract Calculating Differentially Expressed Genes (DEGs) from RNA-sequencing requires replicates to estimate gene-wise variability, a requirement that is at times financially or physiologically infeasible in clinics. By imposing restrictive transcriptome-wide assumptions limiting inferential opportunities of conventional methods (edgeR, NOISeq-sim, DESeq, DEGseq), comparing two conditions without replicates (TCWR) has been proposed, but not evaluated. Under TCWR conditions (e.g., unaffected tissue vs. tumor), differen...
Source: AMIA Annual Symposium Proceedings - June 24, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

High Performance Computing on Flat FHIR Files Created with the New SMART/HL7 Bulk Data Access Standard.
Authors: Liu D, Sahu R, Ignatov V, Gottlieb D, Mandl KD Abstract The FHIR Bulk Data API is designed to create a uniform capability for population-level exports from clinical systems, into a file format often referred to as "Flat-FHIR." Leveraging the SMART backend services authentication and authorization profile, the approach enables healthcare providers and organizations to define and access cohorts from electronic health records and payor claims data with "push button" simplicity--a substantial advance over the current state, where each site of care needs highly skilled extraction transform a...
Source: AMIA Annual Symposium Proceedings - June 24, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Learning Hierarchical Representations of Electronic Health Records for Clinical Outcome Prediction.
Authors: Liu L, Li H, Hu Z, Shi H, Wang Z, Tang J, Zhang M Abstract Clinical outcome prediction based on Electronic Health Record (EHR) helps enable early interventions for high-risk patients, and is thus a central task for smart healthcare. Conventional deep sequential models fail to capture the rich temporal patterns encoded in the long and irregular clinical event sequences in EHR. We make the observation that clinical events at a long time scale exhibit strong temporal patterns, while events within a short time period tend to be disordered co-occurrence. We thus propose differentiated mechanisms to model clinic...
Source: AMIA Annual Symposium Proceedings - June 24, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Biomedical Research Cohort Membership Disclosure on Social Media.
Authors: Liu Y, Yan C, Yin Z, Wan Z, Xia W, Kantarcioglu M, Vorobeychik Y, Clayton EW, Malin BA Abstract To accelerate medical knowledge discovery, an increasing number of research programs are gathering and sharing data on a large number of participants. Due to the privacy concerns and legal restrictions on data sharing, these programs apply various strategies to mitigate privacy risk. However, the activities of participants and research program sponsors, particularly on social media, might reveal an individual's membership in a study, making it easier to recognize participants' records and uncover the information...
Source: AMIA Annual Symposium Proceedings - June 24, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Foundations for Studying Clinical Workflow: Development of a Composite Inter-Observer Reliability Assessment for Workflow Time Studies.
Authors: Lopetegui M, Yen PY, Embi P, Payne P Abstract The ability to understand and measure the complexity of clinical workflow provides hospital managers and researchers with the necessary knowledge to assess some of the most critical issues in healthcare. Given the protagonist role of workflow time studies on influencing decision makers, major efforts are being conducted to address existing methodological inconsistencies of the technique. Among major concerns, the lack of a standardized methodology to ensure the reliability of human observers stands as a priority. In this paper, we highlight the limitations of t...
Source: AMIA Annual Symposium Proceedings - June 24, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Bootstrapping Adversarial Learning of Biomedical Ontology Alignments.
Authors: Maldonado RM, Harabagiu SM Abstract Learning how to automatically align biomedical ontologies has been a long-standing goal, given their ever-growing content and the many applications that rely on them. Because the knowledge graphs underlying biomedical ontologies enable neural learning techniques to acquire knowledge embeddings as representations of these ontologies, neural learning can also consider ontology alignments. In this paper, we present the Knowledge-graph Alignment & Embedding Generative Adversarial Network (KAEGAN) which learns (a) to represent the relational knowledge from two distinct bi...
Source: AMIA Annual Symposium Proceedings - June 24, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Barriers, Facilitators, and Potential Solutions to Advancing Interoperable Clinical Decision Support: Multi-Stakeholder Consensus Recommendations for the Opioid Use Case.
Authors: Marcial LH, Blumenfeld B, Harle C, Jing X, Keller MS, Lee V, Lin Z, Dover A, Midboe AM, Al-Showk S, Bradley V, Breen J, Fadden M, Lomotan E, Marco-Ruiz L, Mohamed R, O'Connor P, Rosendale D, Solomon H, Kawamoto K Abstract With the advent of interoperability standards such as FHIR, SMART, CDS Hooks, and CQL, interoperable clinical decision support (CDS) holds great promise for improving healthcare. In 2018, the Agency for Healthcare Research and Quality (AHRQ)-sponsored Patient-Centered CDS Learning Network (PCCDS LN) chartered a Technical Framework Working Group (TechFWG) to identify barriers, facilitators...
Source: AMIA Annual Symposium Proceedings - June 24, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Sharing of Individual Participant Data from Clinical Trials: General Comparison and HIV Use Case.
Authors: Mayer CS, Williams N, Gold S, Fung KW, Huser V Abstract Sharing of individual participant data is encouraged by the International Committee of Medical Journal Editors. We analyzed clinical trial registry data from ClinicalTrials.gov (CTG) and determined the proportion of trials sharing de-identified Individual Participant Data (IPD). We looked at 3,138 medical conditions (as Medical Subject Heading terms). Overall, 10.8% of trials with first registration date after December 1, 2015 answered 'Yes' to plan to share de-identified IPD data. This sharing rate ranges between 0% (biliary tract neoplasms) to 72.2%...
Source: AMIA Annual Symposium Proceedings - June 24, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Identification and Ranking of Biomedical Informatics Researcher Citation Statistics through a Google Scholar Scraper.
Authors: McCoy AB, Sittig DF, Lin J, Wright A Abstract To overcome limitations of previously developed scientific productivity ranking services, we created the Biomedical Informatics Researchers ranking website (rank.informatics-review.com). The website is composed of four key components that work together to create the automatically updating ranking website: 1) list of biomedical informatics researchers, 2) Google Scholar scraper, 3) display page, and 4) updater. The interactive website has facilitated identification of leaders in each of the key citation statistics categories (i.e., number of citations, h-index, ...
Source: AMIA Annual Symposium Proceedings - June 24, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

"AMIA Annu Symp Proc"; +115 new citations
115 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: "AMIA Annu Symp Proc" These pubmed results were generated on 2020/04/22PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites. (Source: AMIA Annual Symposium Proceedings)
Source: AMIA Annual Symposium Proceedings - April 22, 2020 Category: Bioinformatics Tags: Report Source Type: research

Identifying Key Players in the Care Process of Patients with Diabetes Using Social Network Analysis and Administrative Data.
This study can positively impact informed decision-making of policymakers and insurance companies to better design their insurance coverage plans based on the collaboration patterns of the healthcare providers. PMID: 30815188 [PubMed - indexed for MEDLINE] (Source: AMIA Annual Symposium Proceedings)
Source: AMIA Annual Symposium Proceedings - January 29, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Assessing Information Congruence of Documented Cardiovascular Disease between Electronic Dental and Medical Records.
Authors: Patel J, Mowery D, Krishnan A, Thyvalikakath T Abstract Dentists are more often treating patients with Cardiovascular Diseases (CVD) in their clinics; therefore, dentists may need to alter treatment plans in the presence of CVD. However, it's unclear to what extent patient-reported CVD information is accurately captured in Electronic Dental Records (EDRs). In this pilot study, we aimed to measure the reliability of patient-reported CVD conditions in EDRs. We assessed information congruence by comparing patients' self-reported dental histories to their original diagnosis assigned by their medical providers ...
Source: AMIA Annual Symposium Proceedings - January 29, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

The Sublanguage of Clinical Problem Lists: A Corpus Analysis.
In this study, we explore the structure of these problem list entries both grammatically and semantically in an attempt to learn the specialized rules, or "sublanguage" that governs them. Our methods focus on a large-scale corpus analysis of problem list entries. Using Resource Description Framework (RDF), we incorporate inferencing and reasoning via domain-specific ontologies into our analysis to elicit common semantic patterns. We also explore how these methods can be applied dynamically to learn specific sublanguage features of interest for a particular concept or topic within the domain. PMID: 30815190 [P...
Source: AMIA Annual Symposium Proceedings - January 29, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Evaluating the Impact of Uncertainty on Risk Prediction: Towards More Robust Prediction Models.
We present a framework for uncertainty analysis that accounts for variability in input values. Uncertain or missing values are replaced with a range of plausible values. These ranges are used to compute individualized risk confidence intervals. We demonstrate our approach using the Gail model to evaluate the impact of uncertainty on management decisions. Up to 13% of cases (uncertain) had a risk interval that falls within the decision threshold (e.g., 1.67% 5-year absolute risk). A small number of cases changed from low- to high-risk when missing values were present. Our analysis underscores the need for better communicati...
Source: AMIA Annual Symposium Proceedings - January 29, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Low Screening Rates for Diabetes Mellitus Among Family Members of Affected Relatives.
This study demonstrates that informatics methods applied to electronic health record data can be used to identify patients at risk for disease development, and therefore support clinical care. PMID: 30815192 [PubMed - indexed for MEDLINE] (Source: AMIA Annual Symposium Proceedings)
Source: AMIA Annual Symposium Proceedings - January 29, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Systematic Literature Review of Prescription Drug Monitoring Programs.
Authors: Ponnapalli A, Grando A, Murcko A, Wertheim P Abstract Prescription opioid abuse has become a serious national problem. To respond to the opioid epidemic, states have implemented prescription drug monitoring programs (PDMPs) to monitor and reduce opioid abuse. We conducted a systematic literature review to better understand the PDMP impact on reducing opioid abuse, improving prescriber practices, and how EHR integration has impacted PDMP usability. Lessons learned can help guide federal and state-based efforts to better respond to the opioid crisis. PMID: 30815193 [PubMed - indexed for MEDLINE] (Source:...
Source: AMIA Annual Symposium Proceedings - January 29, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

When an Alert is Not an Alert: A Pilot Study to Characterize Behavior and Cognition Associated with Medication Alerts.
Authors: Reese TJ, Kawamoto K, Fiol GD, Drews F, Taft T, Kramer H, Weir C Abstract Introduction. Preventable adverse drug events are a significant patient-safety concern, yet most medication alerts are disregarded. Pharmacists encounter the highest number of medication alerts and likely have developed behaviors to cope with alerting inefficiencies. The study objective was to better understand alert override behavior relating to a motivational construct framework. Methods. Mixed-methods study of 10 pharmacists (567 verifications) with eye-tracking observations and retrospective think aloud interviews. Results. Pharm...
Source: AMIA Annual Symposium Proceedings - January 29, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Identifying Cases of Metastatic Prostate Cancer Using Machine Learning on Electronic Health Records.
Authors: Seneviratne MG, Banda JM, Brooks JD, Shah NH, Hernandez-Boussard TM Abstract Cancer stage is rarely captured in structured form in the electronic health record (EHR). We evaluate the performance of a classifier, trained on structured EHR data, in identifying prostate cancer patients with metastatic disease. Using EHR data for a cohort of 5,861 prostate cancer patients mapped to the Observational Health Data Sciences and Informatics (OHDSI) data model, we constructed feature vectors containing frequency counts of conditions, procedures, medications, observations and laboratory values. Staging information fr...
Source: AMIA Annual Symposium Proceedings - January 29, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Incorporating Knowledge-Driven Insights into a Collaborative Filtering Model to Facilitate the Differential Diagnosis of Rare Diseases.
In this study, we sought to incorporate a knowledge-driven approach into collaborative filtering to optimize results learned from clinical data. Our results demonstrated an improvement in performance over pure data-driven approaches with the potential to facilitate the differential diagnosis of rare diseases. PMID: 30815196 [PubMed - indexed for MEDLINE] (Source: AMIA Annual Symposium Proceedings)
Source: AMIA Annual Symposium Proceedings - January 29, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Communication Technology Use and Preferences for Pregnant Women and Their Caregivers.
Authors: Shroder M, Anders SH, Dorst M, Jackson GP Abstract The rapid evolution of communication technologies has created new ways for healthcare consumers to manage their health. In a mixed-methods study, we examined technology use and willingness to use in pregnant women and caregivers, using surveys and semi-structured interviews. Most participants had used text messaging, automated phone calls, Skype/FaceTime, social media, and online discussion forums. To communicate with healthcare providers, most were willing to use text messaging and had not, but desired to use Skype/FaceTime. Fewer were willing to use soci...
Source: AMIA Annual Symposium Proceedings - January 29, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Integration of Transcriptomic Data Identifies Global and Cell-Specific Asthma-Related Gene Expression Signatures.
Authors: Kan M, Shumyatcher M, Diwadkar A, Soliman G, Himes BE Abstract Over 140,000 transcriptomic studies performed in healthy and diseased cell and tissue types, at baseline and after exposure to various agents, are available in public repositories. Integrating results of transcriptomic datasets has been an attractive approach to identify gene expression signatures that are more robust than those obtained for individual datasets, especially datasets with small sample size. We developed Reproducible Analysis and Validation of Expression Data (RAVED), a pipeline that facilitates the creation of R Markdown reports ...
Source: AMIA Annual Symposium Proceedings - January 12, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

DrKnow: A Diagnostic Learning Tool with Feedback from Automated Clinical Decision Support.
We present the design of DrKnow, a web-based learning application that utilises a clinical decision support system (CDSS) and virtual cases to support the development of problem-solving and decision-making skills in medical students. Based on the clinical information they request and prioritise, DrKnow provides personalised feedback to help students develop differential and provisional diagnoses at key decision points as they work through the virtual cases. Once students make a final diagnosis, DrKnow presents students with information about their overall diagnostic performance as well as recommendations for diagnosing sim...
Source: AMIA Annual Symposium Proceedings - January 12, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Integrated machine learning pipeline for aberrant biomarker enrichment (i-mAB): characterizing clusters of differentiation within a compendium of systemic lupus erythematosus patients.
Authors: Le TT, Blackwood NO, Taroni JN, Fu W, Breitenstein MK Abstract Clusters of differentiation (CD) are cell surface biomarkers that denote key biological differences between cell types and disease state. CD-targeting therapeutic monoclonal antibodies (mABs) afford rich trans-disease repositioning opportunities. Within a compendium of systemic lupus erythematous (SLE) patients, we applied the Integrated machine learning pipeline for aberrant biomarker enrichment (i-mAB) to profile de novo gene expression features affecting CD20, CD22 and CD30 gene aberrance. First, a novel Relief-based algorithm identified int...
Source: AMIA Annual Symposium Proceedings - January 12, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Mining clinical big data for drug safety: Detecting inadequate treatment with a DNA sequence alignment algorithm.
We describe the adaptation of the Smith-Waterman algorithm, and the implemented user interface. The evaluation with pharmacovigilance use cases involved the detection of inadequate treatment decisions in patient sequences. The precision and recall results (F-measure = 0.87) suggest that our adaptation of the Smith-Waterman-based algorithm is well-suited for this type of pharmacovigilance activities. The user interface allowed the rapid identification of cases of inadequate treatment. PMID: 30815181 [PubMed - indexed for MEDLINE] (Source: AMIA Annual Symposium Proceedings)
Source: AMIA Annual Symposium Proceedings - January 12, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Balancing Performance and Interpretability: Selecting Features with Bootstrapped Ridge Regression.
Authors: Lenert MC, Walsh CG Abstract Informctticists sometimes attempt to predict chronic healthcare events that are not fully understood. The resulting models often incorporate copious numbers of predictors derived across diverse datasets. This approach may yield desirable performance characteristics, but it sacrifices interpretability and portability. The Bootstrapped Ridge Selector (BoRidge) offers a tool to balance performance with interpretability. Compared to two modern feature selection methods, Bootstrapped LASSO regression (BoLASSO) and a minimal-redundancy-maximal-relevance selector (mRMR), the BoRidge b...
Source: AMIA Annual Symposium Proceedings - January 12, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Secondary Use of Electronic Health Record Data for Prediction of Outpatient Visit Length in Ophthalmology Clinics.
In this study, we address this challenge by developing and validating analytic models for predicting patient encounter length based on secondary EHR data. Key findings from this study are: (1) Secondary use of EHR data may be captured to predict provider interaction time with patients; (2) Modeling results using secondary data may provide more accurate predictions of provider interaction time than an expert provide; (3) These findings suggest that secondary use of EHR data may be used to develop effective customized scheduling methods to improve clinical efficiency. In the future, this has the potential to contribute towar...
Source: AMIA Annual Symposium Proceedings - January 12, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Using Neural Multi-task Learning to Extract Substance Abuse Information from Clinical Notes.
Authors: Lybarger K, Yetisgen M, Ostendorf M Abstract Substance abuse carries many negative health consequences. Detailed information about patients' substance abuse history is usually captured in free-text clinical notes. Automatic extraction of substance abuse information is vital to assess patients' risk for developing certain diseases and adverse outcomes. We introduce a novel neural architecture to automatically extract substance abuse information. The model, which uses multi-task learning, outperformed previous work and several baselines created using discrete models. The classifier obtained 0.88-0.95 F1 for ...
Source: AMIA Annual Symposium Proceedings - January 12, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Utility of General and Specific Word Embeddings for Classifying Translational Stages of Research.
Authors: Major V, Surkis A, Aphinyanaphongs Y Abstract Conventional text classification models make a bag-of-words assumption reducing text into word occurrence counts per document. Recent algorithms such as word2vec are capable of learning semantic meaning and similarity between words in an entirely unsupervised manner using a contextual window and doing so much faster than previous methods. Each word is projected into vector space such that similar meaning words such as "strong" and "powerful" are projected into the same general Euclidean space. Open questions about these embeddings include th...
Source: AMIA Annual Symposium Proceedings - January 12, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Trust and Sharing in an Interprofessional Environment: A Thematic Analysis From Child Development Support Work in the Community.
Authors: Mikles SP, Haldar S, Lin SY, Kientz JA, Turner AM Abstract Health information technology (HIT) could aid collaboration in the complex, interprofessional space of child development. Trust between stakeholders is necessary to support collaboration, but extant research provides little guidance on designing HIT that promotes trust within interprofessional collaborations. We analyzed interview data obtained from a heterogeneous group of stakeholders (n = 46) including parents and various service providers to explore trust relationships in the child development space. Our thematic analysis revealed that stakehol...
Source: AMIA Annual Symposium Proceedings - January 12, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Must We Bust the Trust?: Understanding How the Clinician-Patient Relationship Influences Patient Engagement in Safety.
We describe our findings and discuss the implications for the design of patient-facing interventions to promote patient engagement in safety. Our findings shed light on how patient-facing safety interventions can be designed to effectively engage patients and caregivers. PMID: 30815187 [PubMed - indexed for MEDLINE] (Source: AMIA Annual Symposium Proceedings)
Source: AMIA Annual Symposium Proceedings - January 12, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

A Frame-Based NLP System for Cancer-Related Information Extraction.
Authors: Si Y, Roberts K Abstract We propose a frame-based natural language processing (NLP) method that extracts cancer-related information from clinical narratives. We focus on three frames: cancer diagnosis, cancer therapeutic procedure, and tumor description. We utilize a deep learning-based approach, bidirectional Long Short-term Memory (LSTM) Conditional Random Field (CRF), which uses both character and word embeddings. The system consists of two constituent sequence classifiers: a frame identification (lexical unit) classifier and a frame element classifier. The classifier achieves an F1 of 93.70 for cancer ...
Source: AMIA Annual Symposium Proceedings - January 12, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

FABLE: A Semi-Supervised Prescription Information Extraction System.
Authors: Tao C, Filannino M, Uzuner Ö Abstract Prescription information is an important component of electronic health records (EHRs). This information contains detailed medication instructions that are crucial for patients' well-being and is often detailed in the narrative portions of EHRs. As a result, narratives of EHRs need to be processed with natural language processing (NLP) methods that can extract medication and prescription information from free text. However, automatic methods for medication and prescription extraction from narratives face two major challenges: (1) dictionaries can fall short even w...
Source: AMIA Annual Symposium Proceedings - January 12, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Identification of Rare Adverse Events with Year-varying Reporting Rates for FLU4 Vaccine in VAERS.
Authors: Tong J, Huang J, Du J, Cai Y, Tao C, Chen Y Abstract In 2012, a new influenza vaccine - FLU4 was first licensed in the US. FLU4 is a quadrivalent flu vaccine, which can protect against four flu viruses. Compared to FLU and FLU3, FLU4 gives broader protection against the flu viruses. To our knowledge, few studies have focused on the FLU4 vaccine and its adverse events. Since safety signal detection is important in vaccination, it is necessary to launch such studies on FLU4. In this paper, we used the Vaccine Adverse Event Reporting System (VAERS), which is a national post-marketing vaccine safety surveillan...
Source: AMIA Annual Symposium Proceedings - January 12, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Clinical text annotation - what factors are associated with the cost of time?
In this study, we aimed to investigate how factors inherent to the text affect annotation time for a named entity recognition (NER) task. We recruited 9 users to annotate a clinical corpus and recorded annotation time for each sample. Then we defined a set of factors that we hypothesized might affect annotation time, and fitted them into a linear regression model to predict annotation time. The linear regression model achieved an R2 of 0.611, and revealed eight time-associated factors, including characteristics of sentences, individual users, and annotation order with implications for the practice of annotation, and the de...
Source: AMIA Annual Symposium Proceedings - January 12, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Approaches to Link Geospatially Varying Social, Economic, and Environmental Factors with Electronic Health Record Data to Better Understand Asthma Exacerbations.
We describe how EHR-derived data can be enhanced via linking of external sources of social, economic and environmental data when patient-related geospatial information is available, and we illustrate an approach to better understand the geospatial patterns of asthma exacerbation rates in Philadelphia. Specifically, we relate the spatial distribution of asthma exacerbations observed in EHR-derived data to that of known and potential risk factors (i.e., economic deprivation, crime, vehicular traffic, tree cover). Areas of highest risk based on integrated social and environmental data were consistent with an area with increas...
Source: AMIA Annual Symposium Proceedings - January 12, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Visual Explanations From Deep 3D Convolutional Neural Networks for Alzheimer's Disease Classification.
Authors: Yang C, Rangarajan A, Ranka S Abstract We develop three efficient approaches for generating visual explanations from 3D convolutional neural networks (3D-CNNs) for Alzheimer's disease classification. One approach conducts sensitivity analysis on hierarchical 3D image segmentation, and the other two visualize network activations on a spatial map. Visual checks and a quantitative localization benchmark indicate that all approaches identify important brain parts for Alzheimer's disease diagnosis. Comparative analysis show that the sensitivity analysis based approach has difficulty handling loosely distributed...
Source: AMIA Annual Symposium Proceedings - January 12, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Toward Reporting Support and Quality Assessment for Learning from Reporting: A Necessary Data Elements Model for Narrative Medication Error Reports.
This study holds promise in bridging the gap between the low quality of narrative reports and the needs of analyzing and learning from medication errors. PMID: 30815204 [PubMed - indexed for MEDLINE] (Source: AMIA Annual Symposium Proceedings)
Source: AMIA Annual Symposium Proceedings - January 12, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Learning When Communications Between Healthcare Providers Indicate Hormonal Therapy Medication Discontinuation.
Authors: Yin Z, Warner JL, Malin BA Abstract Hormonal therapy is an effective yet challenging long-term treatment for patients with hormone receptor positive breast cancer. Understanding what factors indicate discontinuation of a recommended hormonal therapy medication can help improve treatment experience. To date, studies on medication discontinuation have focused on patient information gathered through questionnaires, structured electronic medical records and online discussion boards. However, there has been little investigation into the communications between healthcare providers, which may provide additional i...
Source: AMIA Annual Symposium Proceedings - January 12, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research

Computable Eligibility Criteria through Ontology-driven Data Access: A Case Study of Hepatitis C Virus Trials.
Authors: Zhang H, He Z, He X, Guo Y, Nelson DR, Modave F, Wu Y, Hogan W, Prosperi M, Bian J Abstract The increasing adoption of electronic health record (EHR) systems and proliferation of clinical data offer unprecedented opportunities for cohort identification to accelerate patient recruitment. However, the effort required to translate trial eligibility criteria to the correct cohort identification queries for clinical investigators is substantial, at least in part due to the lack of clear definitions in both the free-text eligibility criteria and the data models used to structure the available data elements in ta...
Source: AMIA Annual Symposium Proceedings - January 12, 2020 Category: Bioinformatics Tags: AMIA Annu Symp Proc Source Type: research