429 results match your criteria AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science[Journal]


A Novel Representation of Vaccine Efficacy Trial Datasets for Use in Computer Simulation of Vaccination Policy.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:389-398. Epub 2018 May 18.

Department of Family Medicine, University of Pittsburgh, Pittsburgh, PA, USA.

Computer simulation is the only method available for evaluating vaccination policy for rare diseases or emergency use of new vaccines. The most realistic simulation of vaccination policy is agent-based simulation (ABS) in which agents have similar socio-demographic characteristics to a population of interest. Currently, analysts use published information about vaccine efficacy (VE) as the probability that a vaccinated agent develops immunity; however, VE trials typically report only a single overall VE, or VE conditioned on one covariate (e. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961808PMC
May 2018
21 Reads

Characterizing Functional Health Status of Surgical Patients in Clinical Notes.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:379-388. Epub 2018 May 18.

University of Minnesota Department of Surgery, Minneapolis, MN.

Functional health status is an important factor not only for determining overall health, but also for measuring risks of adverse events. Our hypothesis is that important functional status data is contained in clinical notes. We found that several categories of phrases related to functional status including diagnoses, activity and care assessments, physical exam, functional scores, assistive equipment, symptoms, and surgical history were important factors. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961772PMC
May 2018
3 Reads

i2b2 implemented over SMART-on-FHIR.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:369-378. Epub 2018 May 18.

LIMSI, CNRS, Universit├ę Paris-Saclay, Orsay, France.

Integrating Biology and the Bedside (i2b2) is the de-facto open-source medical tool for cohort discovery. Fast Healthcare Interoperability Resources (FHIR) is a new standard for exchanging health care information electronically. Substitutable Modular third-party Applications (SMART) defines the SMART-on-FHIR specification on how applications shall interface with Electronic Health Records (EHR) through FHIR. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961782PMC
May 2018
8 Reads

Predicting Neonatal Encephalopathy From Maternal Data in Electronic Medical Records.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:359-368. Epub 2018 May 18.

Duke University, Durham, NC.

Neonatal encephalopathy (NE) is a leading cause of neonatal mortality and lifetime neurological disability. The earlier the risk of NE can be assessed, the more effective interventions can be in preventing adverse outcomes. Existing studies that focus on intrapartum risk factors do not provide the early prognostic forecasting necessary to prepare healthcare professionals to intervene early in a high-risk NE case. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961831PMC
May 2018
6 Reads

Trend Analysis of Aggregate Outcomes in Complex Health Survey Data.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:349-358. Epub 2018 May 18.

Alpert Medical School and Center for Biomedical Informatics, Brown University, Providence, RI.

Public health and clinical practice pattern trends are often analyzed using complex survey data. Use of statistical approaches that do not account for survey design predisposes to error, potentially leading to resource misdirection and inefficiency. This study examined two techniques for analyzing trends in complex survey data: (1) design-corrected logistic regression and (2) jackknife re-weighted linear regression. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961819PMC
May 2018
2 Reads

Emergency Department Clinician Perspectives on the Data Availability to Implement Clinical Decision Support Tools for Five Clinical Practice Guidelines.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:340-348. Epub 2018 May 18.

Duke University School of Nursing, Durham, North Carolina, USA.

Clinical practice guidelines (CPGs) often serve as the knowledge base for clinical decision support (CDS). While CPGs are rigorously created by medical professional societies, the concepts in each guideline may not be sufficient for translation into CDS applications. In addition, clinicians' perceptions of these concepts may differ greatly, affecting the implementation and impact of CDS within an organization. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961800PMC
May 2018
2 Reads

Prototype of a Standards-Based EHR and Genetic Test Reporting Tool Coupled with HL7-Compliant Infobuttons.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:330-339. Epub 2018 May 18.

Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota.

Integration of genetic information is becoming increasingly important in clinical practice. However, genetic information is often ambiguous and difficult to understand, and clinicians have reported low-self-efficacy in integrating genetics into their care routine. The Health Level Seven (HL7) Infobutton standard helps to integrate online knowledge resources within Electronic Health Records (EHRs) and is required for EHR certification in the US. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961781PMC
May 2018
3 Reads

The Data Gap in the EHR for Clinical Research Eligibility Screening.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:320-329. Epub 2018 May 18.

Department of Biomedical Informatics, Columbia University, New York City, New York.

Much effort has been devoted to leverage EHR data for matching patients into clinical trials. However, EHRs may not contain all important data elements for clinical research eligibility screening. To better design research-friendly EHRs, an important step is to identify data elements frequently used for eligibility screening but not yet available in EHRs. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961795PMC
May 2018
2 Reads

Predicting Mortality in Diabetic ICU Patients Using Machine Learning and Severity Indices.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:310-319. Epub 2018 May 18.

Alpert Medical School, Brown University, Providence, RI, USA.

Diabetes constitutes a significant health problem that leads to many long term health issues including renal, cardiovascular, and neuropathic complications. Many of these problems can result in increased health care costs, as well risk of ICU stay and mortality. To date, no published study has used predictive modeling to examine the relative influence of diabetes, diabetic health maintenance, and comorbidities on outcomes in ICU patients. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961793PMC
May 2018
5 Reads

Using a Bedside Interactive Technology to Solicit and Record Pediatric Pain Reassessments: Parent and Nursing Perspectives on a Novel Workflow.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:300-309. Epub 2018 May 18.

Department of Pediatrics, University of Minnesota, Minneapolis, MN.

To measure the impact of a novel interactive inpatient pediatric pain management solution integrating our hospital's electronic health record system, the nurse communication phones, and the pharmacy dispensing system, we assessed parent and nurse perspectives on the tool's potential value, benefits, and challenges. A mixed-methods approach with survey instruments containing closed-ended and open-ended questions was administered to 30 parents and 59 nurses (66% and 23% response rate respectively). Overall, parents were more satisfied with the interactive technology experience (90%) compared to nurses (50%) with both indicating timely reassessments of pain being the most valuable feature. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961804PMC
May 2018
6 Reads

Identifying Diagnostic Paths for Undifferentiated Abdominal Pain from Electronic Health Record Data.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:290-299. Epub 2018 May 18.

Case Western Reserve University School of Medicine, Cleveland, OH.

The diagnostic process is a complex, uncertain, and highly variable process which is under-studied and lacks evidence from randomized clinical trials. This study used a novel visual analytics method to identify and visualize diagnostic paths for undifferentiated abdominal pain, by leveraging electronic health record (EHR) data of 501 patients in the ambulatory setting of a single institution. A total of 63 patients reached diagnoses in the study sample. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961779PMC
May 2018
2 Reads

Adapting Word Embeddings from Multiple Domains to Symptom Recognition from Psychiatric Notes.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:281-289. Epub 2018 May 18.

School of Biomedical Informatics, The University of Texas Health Science Centerat Houston, Houston, TX, USA.

Mental health is increasingly recognized an important topic in healthcare. Information concerning psychiatric symptoms is critical for the timely diagnosis of mental disorders, as well as for the personalization of interventions. However, the diversity and sparsity of psychiatric symptoms make it challenging for conventional natural language processing techniques to automatically extract such information from clinical text. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961810PMC
May 2018
30 Reads

A Crowdsourcing Framework for Medical Data Sets.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:273-280. Epub 2018 May 18.

Vanderbilt University, Nashville, TN, USA.

Crowdsourcing services like Amazon Mechanical Turk allow researchers to ask questions to crowds of workers and quickly receive high quality labeled responses. However, crowds drawn from the general public are not suitable for labeling sensitive and complex data sets, such as medical records, due to various concerns. Major challenges in building and deploying a crowdsourcing system for medical data include, but are not limited to: managing access rights to sensitive data and ensuring data privacy controls are enforced; identifying workers with the necessary expertise to analyze complex information; and efficiently retrieving relevant information in massive data sets. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961774PMC
May 2018
3 Reads

Application of Data Provenance in Healthcare Analytics Software: Information Visualisation of User Activities.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:263-272. Epub 2018 May 18.

King's College London, London, United Kingdom.

Data provenance is a technique that describes the history of digital objects. In health data settings, it can be used to deliver auditability and transparency, and to achieve trust in a software system. However, implementing data provenance in analytics software at an enterprise level presents a different set of challenges from the research environments where data provenance was originally devised. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961786PMC
May 2018
4 Reads

A Deep Learning Approach to Examine Ischemic ST Changes in Ambulatory ECG Recordings.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:256-262. Epub 2018 May 18.

Department of Physiological Nursing, University of California, San Francisco, CA.

Patients with suspected acute coronary syndrome (ACS) are at risk of transient myocardial ischemia (TMI), which could lead to serious morbidity or even mortality. Early detection of myocardial ischemia can reduce damage to heart tissues and improve patient condition. Significant ST change in the electrocardiogram (ECG) is an important marker for detecting myocardial ischemia during the rule-out phase of potential ACS. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961830PMC
May 2018
33 Reads

Exploring the Potential of Direct-To-Consumer Genomic Test Data for Predicting Adverse Drug Events.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:247-256. Epub 2018 May 18.

Center for Biomedical Informatics, Brown University, Providence, RI.

Recent technological advancements in genetic testing and the growing accessibility of public genomic data provide researchers with a unique avenue to approach personalized medicine. This feasibility study examined the potential of direct-to-consumer (DTC) genomic tests (focusing on 23andMe) in research and clinical applications. In particular, we combined population genetics information from the Personal Genome Project with adverse event reports from AEOLUS and pharmacogenetic information from PharmGKB. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961769PMC
May 2018
2 Reads

CHCi - A Dynamic Data Platform for Clinical Data Capture and Use.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:246-255. Epub 2018 May 18.

Division of Pediatric Cardiology, University of Michigan, Ann Arbor, MI.

All academic medical centers have a strong desire to maximize the value of their clinical data for secondary use purposes such as quality improvement (QI) and research. However, this need has not been adequately fulfilled due in part to the fact that the data capture functions in current electronic health record systems predominantly focus on clinical documentation and billing, lacking the flexibility to allow the collection of additional data elements critical to QI or research. To address this gap, we designed and developed a dynamic data platform to support clinicians' varied needs for recording additional data about their patients outside of direct patient care (e. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961796PMC
May 2018
25 Reads

Learning Opportunities for Drug Repositioning via GWAS and PheWAS Findings.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:237-246. Epub 2018 May 18.

Vanderbilt University, Nashville, TN.

Drug repositioning for available medications can be preferred over traditional drug development, which requires substantially more effort to uncover new insights into medications and diseases. Genome-Wide Association Studies (GWAS) and Phenome-Wide Association Studies (PheWAS) are two complimentary methods for finding novel associations between genes and diseases. We hypothesize that discoveries from these studies could be leveraged to find new targets for existing drugs. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961790PMC
May 2018
3 Reads

Evaluation of Flowsheet Documentation in the Electronic Health Record for Residence, Living Situation, and Living Conditions.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:236-245. Epub 2018 May 18.

Institute for Health Informatics, University of Minnesota, Minneapolis, MN.

Social determinants of health (SDOH) are important considerations in diagnosis, prevention, and health outcomes. However, they are often not well documented in the EHR and found primarily in unstructured or semi-structured text. Building upon previous work, we analyzed all flowsheet data in 2013 for information related to the SDOH topic areas of Residence, Living Situation, and Living Conditions. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961798PMC
May 2018
2 Reads

Comparison of Different Classifiers with Active Learning to Support Quality Control in Nucleus Segmentation in Pathology Images.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:227-236. Epub 2018 May 18.

Stony Brook University, Stony Brook, NY, USA.

Segmentation of nuclei in whole slide tissue images is a common methodology in pathology image analysis. Most segmentation algorithms are sensitive to input algorithm parameters and the characteristics of input images (tissue morphology, staining, etc.). Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961826PMC
May 2018
22 Reads

Inpatient Clinical Order Patterns Machine-Learned From Teaching Versus Attending-Only Medical Services.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:226-235. Epub 2018 May 18.

Department of Medicine, Stanford University, Stanford, CA, USA.

Clinical order patterns derived from data-mining electronic health records can be a valuable source of decision support content. However, the quality of crowdsourcing such patterns may be suspect depending on the population learned from. For example, it is unclear whether learning inpatient practice patterns from a university teaching service, characterized by physician-trainee teams with an emphasis on medical education, will be of variable quality versus an attending-only medical service that focuses strictly on clinical care. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961816PMC
May 2018
5 Reads

Predicting Low Information Laboratory Diagnostic Tests.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:217-226. Epub 2018 May 18.

Department of Medicine, Stanford University, Stanford, CA, USA.

Escalating healthcare costs and inconsistent quality is exacerbated by clinical practice variability. Diagnostic testing is the highest volume medical activity, but human intuition is typically unreliable for inferences on diagnostic performance characteristics. Electronic medical records from a tertiary academic hospital (2008-2014) allow us to systematically predict laboratory pre-test probabilities of being normal under different conditions. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961775PMC
May 2018
3 Reads

Applying Probabilistic Decision Models to Clinical Trial Design.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:216-225. Epub 2018 May 18.

Department of Radiation Oncology, University of Washington, Seattle, WA.

Clinical trial design most often focuses on a single or several related outcomes with corresponding calculations of statistical power. We consider a clinical trial to be a decision problem, often with competing outcomes. Using a current controversy in the treatment of HPV-positive head and neck cancer, we apply several different probabilistic methods to help define the range of outcomes given different possible trial designs. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961806PMC
May 2018
4 Reads

Comparing Existing Resources to Represent Dietary Supplements.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:207-216. Epub 2018 May 18.

Institute for Health Informatics, University of Minnesota, Minneapolis, MN.

Dietary supplements, often considered as food, are widely consumed despite of limited knowledge around their safety/efficacy and any well-established regulatory policies, unlike their drug counterparts. Informatics methods may be useful in filling this knowledge gap, however, the lack of standardized representation of DS hinders this progress. In this pilot study, five electronic DS resources, i. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961776PMC
May 2018
3 Reads

Word Repetition in Separate Conversations for Detecting Dementia:A Preliminary Evaluation on Data of Regular Monitoring Service.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:206-215. Epub 2018 May 18.

IBM Research - Tokyo, Tokyo, Japan.

For detecting early signs of dementia, monitoring technology has been actively investigated due to the low diagnostic coverage as well as the requirement for early intervention. Although language features have been used for detecting the language dysfunctions resulting from dementia in neuropsychological tests, features that can be extracted by regular conversations remain unexplored. Here, we propose a feature to characterize the atypical repetition of words on different days which is observed in patients with dementia. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961820PMC
May 2018
2 Reads

Deep Learning data integration for better risk stratification models of bladder cancer.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:197-206. Epub 2018 May 18.

Epidemiology Program, University of Hawaii Cancer Center Honolulu, HI 96813, USA.

We propose an unsupervised multi-omics integration pipeline, using deep-learning autoencoder algorithm, to predict the survival subtypes in bladder cancer (BC). We used TCGA dataset comprising mRNA, miRNA and methylation to infer two survival subtypes. We then constructed a supervised classification model to predict the survival subgroups of any new individual sample. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961799PMC
May 2018
4 Reads

Identifying Supplement Use Within Clinical Notes: An Applicationof Natural Language Processing.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:196-205. Epub 2018 May 18.

Center for Biomedical Informatics, Brown University, Providence, Rhode Island.

Recent statistics indicate that the use of dietary supplements has increased over the years. Although being popular among consumers who use them for a variety of reasons, there have been limited clinical data-driven studies of the impact of dietary supplements on health outcomes. Challenges that impede such analyses in a comprehensive manner include either the sequestered nature of such data or their embedding within biomedical and clinical text. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961809PMC
May 2018
2 Reads

NegBio: a high-performance tool for negation and uncertainty detection in radiology reports.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:188-196. Epub 2018 May 18.

National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA.

Negative and uncertain medical findings are frequent in radiology reports, but discriminating them from positive findings remains challenging for information extraction. Here, we propose a new algorithm, NegBio, to detect negative and uncertain findings in radiology reports. Unlike previous rule-based methods, NegBio utilizes patterns on universal dependencies to identify the scope of triggers that are indicative of negation or uncertainty. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961822PMC
May 2018
2 Reads

Provider Adoption of Speech Recognition and its Impact on Satisfaction, Documentation Quality, Efficiency, and Cost in an Inpatient EHR.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:186-195. Epub 2018 May 18.

Nuance® Communications, Inc., Burlington, Massachusetts.

This study utilizes qualitative and quantitative methods to measure the adoption of speech recognition (SR) and its impact ON provider satisfaction, documentation quality, efficiency, and cost when used for clinical documentation within the electronic health record (EHR). Qualitative surveys gauged providers' expectations and experiences regarding documentation before and after SR implementation. A new methodology was developed to measure SR adoption as a proportion of total documentation volume. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961784PMC
May 2018
23 Reads

A Low Rank Model for Phenotype Imputation in Autism Spectrum Disorder.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:178-187. Epub 2018 May 18.

Stanford University, Stanford, California.

Autism Spectrum Disorder is a highly heterogeneous condition currently diagnosed using behavioral symptoms. A better understanding of the phenotypic subtypes of autism is a necessary component of the larger goal of mapping autism genotype to phenotype. However, as with most clinical records describing human disease, the phenotypic data available for autism contains varying levels of noise and incompleteness that complicate analysis. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961817PMC
May 2018
2 Reads

Feasibility of Homomorphic Encryption for Sharing I2B2 Aggregate-Level Data in the Cloud.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:176-185. Epub 2018 May 18.

Partners Healthcare, Boston, MA, USA.

The biomedical community is lagging in the adoption of cloud computing for the management of medical data. The primary obstacles are concerns about privacy and security. In this paper, we explore the feasibility of using advanced privacy-enhancing technologies in order to enable the sharing of sensitive clinical data in a public cloud. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961814PMC
May 2018
3 Reads

CATCH-KB: Establishing a Pharmacogenomics Variant Repository for Chemotherapy-Induced Cardiotoxicity.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:168-177. Epub 2018 May 18.

Weill Cornell Medicine, New York, USA.

The Cardiotoxicity of Chemotherapy Knowledgebase (CATCH-KB) contains information extracted from articles investigating an association between germline genetic polymorphisms and the development of chemotherapy-induced cardiotoxicity (CIC) in cancer patients receiving antineoplastic treatments. CATCH-KB also contains integrated gene and drug information from open biomedical resources such as PharmGKB and SIDER. Furthermore, the genetic polymorphisms, drugs, and cancer types detailed in CATCH-KB are standardized according to appropriate biomedical ontologies, such as SNOMED-CT and RxNorm. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961780PMC
May 2018
3 Reads

Accurate and interpretable intensive care risk adjustment for fused clinical data with generalized additive models.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:166-175. Epub 2018 May 18.

Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA.

Risk adjustment models for intensive care outcomes have yet to realize the full potential of data unlocked by the increasing adoption of EHRs. In particular, they fail to fully leverage the information present in longitudinal, structured clinical data - including laboratory test results and vital signs - nor can they infer patient state from unstructured clinical narratives without lengthy manual abstraction. A fully electronic ICU risk model fusing these two types of data sources may yield improved accuracy and more personalized risk estimates, and in obviating manual abstraction, could also be used for real-time decision-making. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961794PMC
May 2018
3 Reads

A Computational Approach for Prioritizing Selection of Therapies Targeting Drug Resistant Variation in Anaplastic Lymphoma Kinase.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:160-167. Epub 2018 May 18.

Innovation Center for Biomedical Informatics, Georgetown University Medical Center,Washington, DC, United States of America.

Anaplastic lymphoma kinase (ALK) is a receptor tyrosine kinase implicated as a driver of a number of cancer types, and activates cellular pathways involved in cell proliferation and differentiation. Tyrosine kinase inhibitors (TKIs) are a small molecule therapeutic that blocks ALK function, but tumor evolution leads to the rapid emergence of drug resistant somatic variation and necessitates selection of a new treatment strategy. Computational simulations of protein:drug interactions were used to investigate the impact of seven drug resistant mutations on binding to eleven TKIs approved, or under investigation, for treatment of ALK positive cancers. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961773PMC
May 2018
8 Reads

Memory-Augmented Active Deep Learning for Identifying Relations Between Distant Medical Concepts in Electroencephalography Reports.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:156-165. Epub 2018 May 18.

University of Texas at Dallas, Richardson, TX, U.S.A.

The automatic identification of relations between medical concepts in a large corpus of Electroencephalography (EEG) reports is an important step in the development of an EEG-specific patient cohort retrieval system as well as in the acquisition of EEG-specific knowledge from this corpus. EEG-specific relations involve medical concepts that are not typically mentioned in the same sentence or even the same section of a report, thus requiring extraction techniques that can handle such long-distance dependencies. To address this challenge, we present a novel frame work which combines the advantages of a deep learning framework employing Dynamic Relational Memory (DRM) with active learning. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961777PMC
May 2018
6 Reads

Standardizing And Democratizing Access To Cancer Molecular Diagnostic Test Data From Patients To Drive Translational Research.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:152-159. Epub 2018 May 18.

Baylor College of Medicine and Texas Children's Hospital, Houston, TX.

In the last 3-5 years, there has been a rapid increase in clinical use of next generation sequencing (NGS) based cancer molecular diagnostic (MolDx) testing to develop better treatment plans with targeted therapies. To truly achieve precision oncology, it is critical to catalog cancer sequence variants from MolDx testing for their clinical relevance along with treatment information and patient outcomes, and to do so in a way that supports large-scale data aggregation and new hypothesis generation. Through the NIH-funded Clinical Genome Resource (ClinGen), in collaboration with NLM's ClinVar database and >50 academic and industry based cancer research organizations, a Minimal Variant Level Data (MVLD) framework to standardize reporting and interpretation of drug associated alterations was developed. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961792PMC
May 2018
5 Reads

Automated Detection of Diabetic Retinopathy using Deep Learning.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:147-155. Epub 2018 May 18.

Biomedical Informatics Department, Stanford University, Palo Alto, CA.

Diabetic retinopathy is a leading cause of blindness among working-age adults. Early detection of this condition is critical for good prognosis. In this paper, we demonstrate the use of convolutional neural networks (CNNs) on color fundus images for the recognition task of diabetic retinopathy staging. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961805PMC
May 2018
2 Reads

Pharmacogenomic Approaches for Automated Medication Risk Assessment in People with Polypharmacy.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:142-151. Epub 2018 May 18.

Columbia University, New York,NY, USA.

Medication regimen may be optimized based on individual drug efficacy identified by pharmacogenomic testing. However, majority of current pharmacogenomic decision support tools provide assessment only of single drug-gene interactions without taking into account complex drug-drug and drug-drug-gene interactions which are prevalent in people with polypharmacy and can result in adverse drug events or insufficient drug efficacy. The main objective of this project was to develop comprehensive pharmacogenomic decision support for medication risk assessment in people with polypharmacy that simultaneously accounts for multiple drug and gene effects. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961823PMC
May 2018
3 Reads

Using Machine Learning Algorithms to Predict Risk for Development of Calciphylaxis in Patients with Chronic Kidney Disease.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:139-146. Epub 2018 May 18.

Marshfield Clinic Research Institute, Marshfield, WI.

Calciphylaxis is a disorder that results in necrotic cutaneous lesions with a high rate of mortality. Due to its rarity and complexity, the risk factors for and the disease mechanism of calciphylaxis are not fully understood. This work focuses on the use of machine learning to both predict disease risk and model the contributing factors learned from an electronic health record data set. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961821PMC
May 2018
7 Reads

The Ad-Hoc Uncertainty Principle of Patient Privacy.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:132-138. Epub 2018 May 18.

Harvard Medical School.

The Health Information Portability and Accountability Act (HIPAA) allows for the exchange of de-identified patient data, but its definition of de-identification is essentially open-ended, thus leaving the onus on dataset providers to ensure patient privacy. The Patient Centered Outcomes Research Network (PCORnet) builds a de-identification approach into queries, but we have noticed various subtle problems with this approach. We censor aggregate counts below a threshold (i. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961824PMC
May 2018
23 Reads

Exploring Landscape of Drug-Target-Pathway-Side Effect Associations.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:132-141. Epub 2018 May 18.

Department of Computer Science, Hunter College, the CityUniversity of New York, New York, NY, United States.

Side effects are the second and the fourth leading causes of drug attrition and death in the US. Thus, accurate prediction of side effects and understanding their mechanism of action will significantly impact drug discovery and clinical practice. Here, we show REMAP, a neighborhood-regularized weighted and imputed one-class collaborative filtering algorithm, is effective in predicting drug-side effect associations from a drug-side effect association network, and significantly outperforms the state-of-the-art multi-target learning algorithm for predicting rare side effects. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961812PMC
May 2018
2 Reads

Genetic variation affecting exon skipping contributes to brain structural atrophy in Alzheimer's disease.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:124-131. Epub 2018 May 18.

Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.

Genetic variation in cis-regulatory elements related to splicing machinery and splicing regulatory elements (SREs) results in exon skipping and undesired protein products. We developed a splicing decision model to identify actionable loci among common SNPs for gene regulation. The splicing decision model identified SNPs affecting exon skipping by analyzing sequence-driven alternative splicing (AS) models and by scanning the genome for the regions with putative SRE motifs. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961815PMC
May 2018
14 Reads

Multi-Task Learning to Identify Outcome-Specific Risk Factors that Distinguish Individual Micro and Macrovascular Complications of Type 2 Diabetes.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:122-131. Epub 2018 May 18.

Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA.

Because deterioration in overall metabolic health underlies multiple complications of Type 2 Diabetes Mellitus, a substantial overlap among risk factors for the complications exists, and this makes the outcomes difficult to distinguish. We hypothesized each risk factor had two roles: describing the extent of deteriorating overall metabolic health and signaling a particular complication the patient is progressing towards. We aimed to examine feasibility of our proposed methodology that separates these two roles, thereby, improving interpretation of predictions and helping prioritize which complication to target first. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961813PMC
May 2018
17 Reads

A one-stop shop for biomedical and genomic data.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:118-123. Epub 2018 May 18.

Department of Biomedical Informatics, University of Cincinnati College of Medicine.

The World Wide Web is an indispensable tool for biomedical researchers who are striving to understand the molecular basis of phenotype. However, it presents challenges in the form of proliferation of data resources, with heterogeneity ranging from their content to functionality to interfaces. This often frustrates researchers who must visit multiple sites, become familiar with their interfaces, and learn how to use them to extract knowledge. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961829PMC
May 2018
15 Reads

Predicting Causes of Data Quality Issues in a Clinical Data Research Network.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:113-121. Epub 2018 May 18.

Departments of Pediatrics and Biomedical & Health Informatics, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104.

Clinical data research networks (CDRNs) invest substantially in identifying and investigating data quality problems. While identification is largely automated, the investigation and resolution are carried out manually at individual institutions. In the PEDSnet CDRN, we found that only approximately 35% of the identified data quality issues are resolvable as they are caused by errors in the extract-transform-load (ETL) code. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961770PMC
May 2018
9 Reads

A Network-Biology Informed Computational Drug Repositioning Strategy to Target Disease Risk Trajectories and Comorbidities of Peripheral Artery Disease.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:108-117. Epub 2018 May 18.

Population Health Science and Policy, Mount Sinai Health System, New York, NY.

Currently, drug discovery approaches focus on the design of therapies that alleviate an index symptom by reengineering the underlying biological mechanism in agonistic or antagonistic fashion. For example, medicines are routinely developed to target an essential gene that drives the disease mechanism. Therapeutic overloading where patients get multiple medications to reduce the primary and secondary side effect burden is standard practice. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961807PMC
May 2018
14 Reads

From Sour Grapes to Low-Hanging Fruit: A Case Study Demonstrating a Practical Strategy for Natural Language Processing Portability.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:104-112. Epub 2018 May 18.

Center for Health Informatics and Bioinformatics, NYU Langone Medical Center, New York, New York.

Natural Language Processing (NLP) holds potential for patient care and clinical research, but a gap exists between promise and reality. While some studies have demonstrated portability of NLP systems across multiple sites, challenges remain. Strategies to mitigate these challenges can strive for complex NLP problems using advanced methods (hard-to-reach fruit), or focus on simple NLP problems using practical methods (low-hanging fruit). Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961788PMC

Polypharmacology Within the Full Kinome: a Machine Learning Approach.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:98-107. Epub 2018 May 18.

University of Kentucky, Lexington, KY, USA.

Protein kinases generate nearly a thousand different protein products and regulate the majority of cellular pathways and signal transduction. It is therefore not surprising that the deregulation of kinases has been implicated in many disease states. In fact, kinase inhibitors are the largest class of new cancer therapies. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961802PMC
May 2018
26 Reads

CDISC SHARE, a Global, Cloud-based Resource of Machine-Readable CDISC Standards for Clinical and Translational Research.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:94-103. Epub 2018 May 18.

Clinical Data Interchange Standards Consortium (CDISC), Austin, TX, USA.

The Clinical Data Interchange Standards Consortium (CDISC) is a global non-profit standards development organization that creates consensus-based standards for clinical and translational research. Several of these standards are now required by regulators for electronic submissions of regulated clinical trials' data and by government funding agencies. These standards are free and open, available for download on the CDISC Website as PDFs. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961771PMC

Characterizing drug-related adverse events by joint analysis of biomedical and genomic data: A case study of drug-induced pulmonary fibrosis.

AMIA Jt Summits Transl Sci Proc 2018 18;2017:91-97. Epub 2018 May 18.

Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.

Spontaneous reporting systems such as the FDA's adverse event reporting system (FAERS) present a great resource to mine for and analyze real-world medication usage. Our study is based on a central premise that FAERS captures unsuspected drug-related adverse events (AEs). Since drug-related AEs result for several reasons, no single approach will be able to predict the entire gamut of AEs. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961825PMC