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AMIA Summits on Translational Science Proceedings

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https://www.readbyqxmd.com/read/28815153/high-risk-drug-drug-interactions-between-clinical-practice-guidelines-for-management-of-chronic-conditions
#1
Geoffrey J Tso, Samson W Tu, Mark A Musen, Mary K Goldstein
Clinicians and clinical decision-support systems often follow pharmacotherapy recommendations for patients based on clinical practice guidelines (CPGs). In multimorbid patients, these recommendations can potentially have clinically significant drug-drug interactions (DDIs). In this study, we describe and validate a method for programmatically detecting DDIs among CPG recommendations. The system extracts pharmacotherapy intervention recommendations from narrative CPGs, normalizes the terms, creates a mapping of drugs and drug classes, and then identifies occurrences of DDIs between CPG pairs...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815152/populating-physician-biographical-pages-based-on-emr-data
#2
Feichen Shen, Sunghwan Sohn, Majid Rastegar-Mojarad, Sijia Liu, Joshua J Pankratz, Michael A Hatton, Nancy Sowada, Om K Shrestha, Shawna L Shurson, Hongfang Liu
The physicians' biographical pages are essential in providing information about physicians' specialties. However, physicians may not have biographical pages or the current pages are not comprehensive. We hypothesize that physicians' specialty information can be mined from Electronic Medical Records (EMRs) of their patients. We proposed an automated physician specialty populating (PSP) system that analyzes physician-ascertained diagnoses in EMRs, aggregates them to an appropriate granularity based on the current biographical pages, and populates the biographical pages accordingly...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815151/eye-tracking-for-clinical-decision-support-a-method-to-capture-automatically-what-physicians-are-viewing-in-the-emr
#3
Andrew J King, Harry Hochheiser, Shyam Visweswaran, Gilles Clermont, Gregory F Cooper
Eye-tracking is a valuable research tool that is used in laboratory and limited field environments. We take steps toward developing methods that enable widespread adoption of eye-tracking and its real-time application in clinical decision support. Eye-tracking will enhance awareness and enable intelligent views, more precise alerts, and other forms of decision support in the Electronic Medical Record (EMR). We evaluated a low-cost eye-tracking device and found the device's accuracy to be non-inferior to a more expensive device...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815150/identifying-psychiatric-comorbidities-for-obstructive-sleep-apnea-in-the-biomedical-literature-and-electronic-health-record
#4
Jessica M Haddad, Elizabeth S Chen
Obstructive sleep apnea (OSA) is one of the most common diseases among Americans, affecting between 5 and 20% of the population. While there is existing evidence of numerous comorbid conditions, such as obesity, diabetes, and high blood pressure, the vast majority of this evidence has focused explicitly on cardiovascular morbidities and excluded any mental or behavioral disorders. The goal of this study was to examine psychiatric comorbidities of OSA in two types of sources: (1) biomedical literature in the MEDLINE/PubMed database (focusing on MeSH descriptors) and Semantic MEDLINE Database (SemMedDB; for semantic predications), and (2) electronic health record data in the MIMIC-III database...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815149/classifying-supplement-use-status-in-clinical-notes
#5
Yadan Fan, Lu He, Serguei V S Pakhomov, Genevieve B Melton, Rui Zhang
Clinical notes contain rich information about supplement use that is critical for detecting adverse interactions between supplements and prescribed medications. It is important to know the context in which supplements are mentioned in clinical notes to be able to correctly identify patients that either currently take the supplement or did so in the past. We applied text mining methods to automatically classify supplement use into four status categories: Continuing (C), Discontinued (D), Started (S), and Unclassified (U)...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815148/spatio-temporal-analysis-for-new-york-state-sparcs-data
#6
Xin Chen, Yu Wang, Elinor Schoenfeld, Mary Saltz, Joel Saltz, Fusheng Wang
Increased accessibility of health data provides unique opportunities to discover spatio-temporal patterns of diseases. For example, New York State SPARCS (Statewide Planning and Research Cooperative System) data collects patient level detail on patient demographics, diagnoses, services, and charges for each hospital inpatient stay and outpatient visit. Such data also provides home addresses for each patient. This paper presents our preliminary work on spatial, temporal, and spatial-temporal analysis of disease patterns for New York State using SPARCS data...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815147/triangulating-methodologies-from-software-medicine-and-human-factors-industries-to-measure-usability-and-clinical-efficacy-of-medication-data-visualization-in-an-electronic-health-record-system
#7
Bora Chang, Manoj Kanagaraj, Ben Neely, Noa Segall, Erich Huang
Within the last decade, use of Electronic Health Record (EHR) systems has become intimately integrated into healthcare practice in the United States. However, large gaps remain in the study of clinical usability and require rigorous and innovative approaches for testing usability principles. In this study, validated tools from the core functions that EHRs serve-software, medicine and human factors-were combined to holistically understand and objectively measure usability of medication data displays. The first phase of this study included 132 medical trainee participants who were randomized to one of two simulated EHR environments with either a medication list or a medication timeline visualization...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815146/quantifying-the-relative-change-in-physical-activity-after-total-knee-arthroplasty-using-accelerometer-based-measurements
#8
Vibhu Agarwal, Mathew Smuck, Nigam H Shah
Osteoarthritis is amongst the top five most disabling conditions affecting Americans over 65 years of age and imposes an annual economic burden estimated at $ 89.1 billion. Nearly half of the cost of care of Osteoarthritis is attributable to hospitalizations for total knee arthroplasties (TKA) and total hip arthroplasties (THA). The current clinical practice relies predominantly on subjective assessment of physical function and pain via patient reported outcome measures (PROM) that have proven inadequate for providing a validated, reliable and responsive measure of TKA outcomes...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815145/evolving-research-data-sharing-networks-to-clinical-app-sharing-networks
#9
Kavishwar B Wagholikar, Rahul Jain, Eliel Oliveira, Joshua Mandel, Jeffery Klann, Ricardo Colas, Prasad Patil, Kuladip Yadav, Kenneth D Mandl, Thomas Carton, Shawn N Murphy
Research networks for data sharing are growing into a large platform for pragmatic clinical trials to generate quality evidence for shared medical decision-making. Institutions partnering in the networks have made large investments in developing the infrastructure for sharing data. We investigate whether institutions partnering on Patient-Centered Outcomes Research Institute's (PCORI) network can share clinical apps. At two different sites, we imported patient data in PCORI's clinical data model (CDM) format into i2b2 repositories, and adapted the SMART-on-FHIR cell to perform CDM-to-FHIR translation, serving demographics, laboratory results and diagnoses...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815144/a-clinical-decision-support-system-for-monitoring-post-colonoscopy-patient-follow-up-and-scheduling
#10
Roxanne Wadia, Mark Shifman, Forrest L Levin, Luis Marenco, Cynthia A Brandt, Kei-Hoi Cheung, Tamar Taddei, Michael Krauthammer
This paper describes a natural language processing (NLP)-based clinical decision support (CDS) system that is geared towards colon cancer care coordinators as the end users. The system is implemented using a metadata- driven Structured Query Language (SQL) function (discriminant function). For our pilot study, we have developed a training corpus consisting of 2,085 pathology reports from the VA Connecticut Health Care System (VACHS). We categorized reports as "actionable"- requiring close follow up, or "non-actionable"- requiring standard or no follow up...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815143/analyzing-electronic-medical-records-to-predict-risk-of-dit-death-intubation-or-transfer-to-icu-in-pediatric-respiratory-failure-or-related-conditions
#11
Teeradache Viangteeravat, Oguz Akbilgic, Robert Lowell Davis
Large volumes of data are generated in hospital settings, including clinical and physiological data generated during the course of patient care. Our goal, as proof of concept, was to identify early clinical factors or traits useful for predicting the outcome, of death, intubation, or transfer to ICU, for children with pediatric respiratory failure. We implemented both supervised and unsupervised methods to extend our understanding on statistical relationships in clinical and physiological data. As a supervised learning method, we use binary logistic regression to predict the risk of developing DIT outcome...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815142/a-data-capture-framework-for-large-scale-interventional-studies-with-survey-workflow-management
#12
Shiqiang Tao, Ningzhou Zeng, Xi Wu, Xiaojin Li, Wei Zhu, Licong Cui, G Q Zhang
Capturing high-quality survey data is an arduous process for large-scale and extensive interventional studies. This paper presents the architecture, interface design, and an innovative form generation engine of a system called RE- Form: Refactorized Electronic Web Forms. REForm provides researchers the capability to design and manage surveys and the flexibility to organize them in a customizable workflow. REForm has been designed, implemented, pilot-tested and deployed for an NCI-funded interventional study IMPACT...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815141/identifying-metastases-related-information-from-pathology-reports-of-lung-cancer-patients
#13
Ergin Soysal, Jeremy L Warner, Joshua C Denny, Hua Xu
Metastatic patterns of spread at the time of cancer recurrence are one of the most important prognostic factors in estimation of clinical course and survival of the patient. This information is not easily accessible since it's rarely recorded in a structured format. This paper describes a system for categorization of pathology reports by specimen site and the detection of metastatic status within the report. A clinical NLP pipeline was developed using sentence boundary detection, tokenization, section identification, part-of-speech tagger, and chunker with some rule based methods to extract metastasis site and status in combination with five types of information related to tumor metastases: histological type, grade, specimen site, metastatic status indicators and the procedure...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815140/d2refine-a-platform-for-clinical-research-study-data-element-harmonization-and-standardization
#14
Deepak K Sharma, Harold R Solbrig, Eric Prud'hommeaux, Kate Lee, Jyotishman Pathak, Guoqian Jiang
In this paper, we present a platform known as D2Refine for facilitating clinical research study data element harmonization and standardization. D2Refine is developed on top of OpenRefine (formerly Google Refine) and leverages simple interface and extensible architecture of OpenRefine. D2Refine empowers the tabular representation of clinical research study data element definitions by allowing it to be easily organized and standardized using reconciliation services. D2Refine builds on valuable built-in data transformation features of OpenRefine to bring source data sets to a finer state quickly...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815139/semanticfind-locating-what-you-want-in-a-patient-record-not-just-what-you-ask-for
#15
John M Prager, Jennifer J Liang, Murthy V Devarakonda
We present a new model of patient record search, called SemanticFind, which goes beyond traditional textual and medical synonym matches by locating patient data that a clinician would want to see rather than just what they ask for. The new model is implemented by making extensive use of the UMLS semantic network, distributional semantics, and NLP, to match query terms along several dimensions in a patient record with the returned matches organized accordingly. The new approach finds all clinically related concepts without the user having to ask for them...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815138/integrative-network-and-transcriptomics-based-approach-predicts-genotype-specific-drug-combinations-for-melanoma
#16
Kelly E Regan, Philip R O Payne, Fuhai Li
Computational methods for drug combination predictions are needed to identify effective therapies that improve durability and prevent drug resistance in an efficient manner. In this paper, we present SynGeNet, a computational method that integrates transcriptomics data characterizing disease and drug z-score profiles with network mining algorithms in order to predict synergistic drug combinations. We compare SynGeNet to other available transcriptomics-based tools to predict drug combinations validated across melanoma cell lines in three genotype groups: BRAF-mutant, NRAS-mutant and combined...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815137/combining-kernel-and-model-based-learning-for-hiv-therapy-selection
#17
Sonali Parbhoo, Jasmina Bogojeska, Maurizio Zazzi, Volker Roth, Finale Doshi-Velez
We present a mixture-of-experts approach for HIV therapy selection. The heterogeneity in patient data makes it difficult for one particular model to succeed at providing suitable therapy predictions for all patients. An appropriate means for addressing this heterogeneity is through combining kernel and model-based techniques. These methods capture different kinds of information: kernel-based methods are able to identify clusters of similar patients, and work well when modelling the viral response for these groups...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815136/design-recommendations-for-pharmacogenomics-clinical-decision-support-systems
#18
Maher Khelifi, Peter Tarczy-Hornoch, Emily B Devine, Wanda Pratt
The use of pharmacogenomics (PGx) in clinical practice still faces challenges to fully adopt genetic information in targeting drug therapy. To incorporate genetics into clinical practice, many support the use of Pharmacogenomics Clinical Decision Support Systems (PGx-CDS) for medication prescriptions. This support was fueled by new guidelines to incorporate genetics for optimizing drug dosage and reducing adverse events. In addition, the complexity of PGx led to exploring CDS outside the paradigm of the basic CDS tools embedded in commercial electronic health records...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815135/active-deep-learning-based-annotation-of-electroencephalography-reports-for-cohort-identification
#19
Ramon Maldonado, Travis R Goodwin, Sanda M Harabagiu
The annotation of a large corpus of Electroencephalography (EEG) reports is a crucial step in the development of an EEG-specific patient cohort retrieval system. The annotation of multiple types of EEG-specific medical concepts, along with their polarity and modality, is challenging, especially when automatically performed on Big Data. To address this challenge, we present a novel framework which combines the advantages of active and deep learning while producing annotations that capture a variety of attributes of medical concepts...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815134/interrogating-patient-level-genomics-and-mouse-phenomics-towards-understanding-cytokines-in-colorectal-cancer-metastasis
#20
Xiaoshu Cai, Yang Chen, Chunlei Zheng, Rong Xu
Background: Colorectal cancer is the second leading cancer-related death worldwide and a majority of patients die from metastasis. Chronic intestinal inflammation plays an important role in tumor progression of colorectal cancer. However, few study works on systematically predicting colorectal cancer metastasis using inflammatory cytokine genes. Results: We developed a supervised machine learning approach to predict colorectal cancer tumor progression using patient level genomic features. To better understand the role of cytokines, we integrated the metastatic-related genes from mouse phenotypic data...
2017: AMIA Summits on Translational Science Proceedings
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