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AMIA Summits on Translational Science Proceedings

Sijia Liu, Hongfang Liu, Vipin Chaudhary, Dingcheng Li
It is widely acknowledged that natural language processing is indispensable to process electronic health records (EHRs). However, poor performance in relation detection tasks, such as coreference (linguistic expressions pertaining to the same entity/event) may affect the quality of EHR processing. Hence, there is a critical need to advance the research for relation detection from EHRs. Most of the clinical coreference resolution systems are based on either supervised machine learning or rule-based methods. The need for manually annotated corpus hampers the use of such system in large scale...
2016: AMIA Summits on Translational Science Proceedings
Sujun Li, Nuno Bandeira, Xiaofeng Wang, Haixu Tang
Although the privacy issues in human genomic studies are well known, the privacy risks in clinical proteomic data have not been thoroughly studied. As a proof of concept, we reported a comprehensive analysis of the privacy risks in clinical proteomic data. It showed that a small number of peptides carrying the minor alleles (referred to as the minor allelic peptides) at non-synonymous single nucleotide polymorphism (nsSNP) sites can be identified in typical clinical proteomic datasets acquired from the blood/serum samples of individual patient, from which the patient can be identified with high confidence...
2016: AMIA Summits on Translational Science Proceedings
Vivekanand Sharma, Wayne Law, Michael J Balick, Indra Neil Sarkar
The impact of ethnobotanical data from surveys of traditional medicinal uses ofplants can be enhanced through the validation of biomedical knowledge that may be embedded in literature. This study aimed to explore the use of informatics approaches, including natural language processing and terminology resources, for extracting and comparing ethnobotanical leads from biomedical literature indexed in MEDLINE. Using ethnobotanical data for plant species described in Primary Health Care Manuals of the Micronesian islands of Palau and Pohnpei, the results of this study were done relative to disease concepts from the "Mental, Behavioral And Neurodevelopmental Disorders " ICD-9-CM category...
2016: AMIA Summits on Translational Science Proceedings
Travis Goodwin, Sanda M Harabagiu
The wealth of clinical information provided by the advent of electronic health records offers an exciting opportunity to improve the quality of patient care. Of particular importance are the risk factors, which indicate possible diagnoses, and the medications which treat them. By analysing which risk factors and medications were mentioned at different times in patients' EHRs, we are able to construct a patient's clinical chronology. This chronology enables us to not only predict how new patient's risk factors may progress, but also to discover patterns of interactions between risk factors and medications...
2016: AMIA Summits on Translational Science Proceedings
Wen-Wai Yim, Tyler Denman, Sharon W Kwan, Meliha Yetisgen
Hepatocellular carcinoma (HCC) is a deadly disease affecting the liver for which there are many available therapies. Targeting treatments towards specific patient groups necessitates defining patients by stage of disease. Criteria for such stagings include information on tumor number, size, and anatomic location, typically only found in narrative clinical text in the electronic medical record (EMR). Natural language processing (NLP) offers an automatic and scale-able means to extract this information, which can further evidence-based research...
2016: AMIA Summits on Translational Science Proceedings
Sheng Yang, Curtis Tatsuoka, Kaushik Ghosh, Nuria Lacuey-Lecumberri, Samden D Lhatoo, Satya S Sahoo
Recent advances in brain fiber tractography algorithms and diffusion Magnetic Resonance Imaging (MRI) data collection techniques are providing new approaches to study brain white matter connectivity, which play an important role in complex neurological disorders such as epilepsy. Epilepsy affects approximately 50 million persons worldwide and it is often described as a disorder of the cortical network organization. There is growing recognition of the need to better understand the role of brain structural networks in the onset and propagation of seizures in epilepsy using high resolution non-invasive imaging technologies...
2016: AMIA Summits on Translational Science Proceedings
Sarah Poole, Shaun Grannis, Nigam H Shah
High utilizers of emergency departments account for a disproportionate number of visits, often for nonemergency conditions. This study aims to identify these high users prospectively. Routinely recorded registration data from the Indiana Public Health Emergency Surveillance System was used to predict whether patients would revisit the Emergency Department within one month, three months, and six months of an index visit. Separate models were trained for each outcome period, and several predictive models were tested...
2016: AMIA Summits on Translational Science Proceedings
Kate Fultz Hollis
The Health Information Technology for Economic and Clinical Health (HITECH) Act proposes the meaningful use of interoperable electronic health records throughout the United States health care delivery system as a critical national goal. As we have moved from medical records on paper to interoperable electronic health records, the rapid and easy sharing of medical data through the Internet makes medical data insecure. Electronic data is easy to share but many steps to ensure security of the data need to be taken...
2016: AMIA Summits on Translational Science Proceedings
Meredith N Zozus, Rachel L Richesson, Anita Walden, Jessie D Tenenbaum, W E Hammond
A fundamental premise of scientific research is that it should be reproducible. However, the specific requirements for reproducibility of research using electronic health record (EHR) data have not been sufficiently articulated. There is no guidance for researchers about how to assess a given project and identify provisions for reproducibility. We analyze three different clinical research initiatives that use EHR data in order to define a set of requirements to reproduce the research using the original or other datasets...
2016: AMIA Summits on Translational Science Proceedings
Anil Yaman, Shreya Chakrabarti, Anando Sen, Chunhua Weng
Knowledge reuse of cancer trial designs may benefit from a temporal understanding of the evolution of the target populations of cancer studies over time. Therefore, we conducted a retrospective analysis of the trends of cancer trial eligibility criteria between 1999 and 2014. The yearly distributions of eligibility concepts for chemicals and drugs, procedures, observations, and medical conditions extracted from free-text eligibility criteria of 32,000 clinical trials for 89 cancer types were analyzed. We identified the concepts that trend upwards or downwards in all or selected cancer types, and the concepts that show anomalous trends for some cancers...
2016: AMIA Summits on Translational Science Proceedings
Bonnie L Westra, Beverly Christie, Steven G Johnson, Lisiane Pruinelli, Anne LaFlamme, Jung In Park, Suzan G Sherman, Matthew D Byrne, Piper Ranallo, Stuart Speedie
Emerging issues of team-based care, precision medicine, and big data science underscore the need for health information technology (HIT) tools for integrating complex data in consistent ways to achieve the triple aims of improving patient outcomes, patient experience, and cost reductions. The purpose of this study was to demonstrate the feasibility of creating a hierarchical flowsheet ontology in i2b2 using data-derived information models and determine the underlying informatics and technical issues. This study is the first of its kind to use information models that aggregate team-based care across time, disciplines, and settings into 14 information models that were integrated into i2b2 in a hierarchical model...
2016: AMIA Summits on Translational Science Proceedings
Yan Wang, Elizabeth S Chen, Ilo Leppik, Serguei Pakhomov, Indra Neil Sarkar, Genevieve B Melton
Epilepsy is a prevalent chronic neurological disorder afflicting about 50 million people worldwide. There is evidence of a strong relationship between familial risk factors and epilepsy, as well as associations with substance use. The goal of this study was to explore the interactions between familial risk factors and substance use based on structured data from the family and social history modules of an electronic health record system for adult epilepsy patients. A total of 8,957patients with 38,802 family history entries and 8,822 substance use entries were gathered and mined for associations at different levels of granularity for three age groupings (>18, 18-64, and ≥65 years old)...
2016: AMIA Summits on Translational Science Proceedings
Geoffrey J Tso, Kaeli Yuen, Susana Martins, Samson W Tu, Michael Ashcraft, Paul Heidenreich, Brian B Hoffman, Mary K Goldstein
Clinical decision support (CDS) systems with complex logic are being developed. Ensuring the quality of CDS is imperative, but there is no consensus on testing standards. We tested ATHENA-HTN CDS after encoding updated hypertension guidelines into the system. A logic flow and a complexity analysis of the encoding were performed to guide testing. 100 test cases were selected to test the major pathways in the CDS logic flow, and the effectiveness of the testing was analyzed. The encoding contained 26 decision points and 3120 possible output combinations...
2016: AMIA Summits on Translational Science Proceedings
Stanisław Saganowski, Andrzej Misiaszek, Piotr Bródka, Anna Andreasson, Vasa Curcin, Brendan Delaney, Kazimierz Frączkowski
Patient Recorded Outcome Measures (PROMs) are an essential part of quality of life monitoring, clinical trials, improvement studies and other medical tasks. Recently, web and mobile technologies have been explored as means of improving the response rates and quality of data collected. Despite the potential benefit of this approach, there are currently no widely accepted standards for developing or implementing PROMs in CER (Comparative Effectiveness Research). Within the European Union project Transform (Translational Research and Patient Safety in Europe) an eHealth solution for quality of life monitoring has been developed and validated...
2016: AMIA Summits on Translational Science Proceedings
Wei Wei, Rebecca Marmor, Siddharth Singh, Shuang Wang, Dina Demner-Fushman, Tsung-Ting Kuo, Chun-Nan Hsu, Lucila Ohno-Machado
Recommendation of related articles is an important feature of the PubMed. The PubMed Related Citations (PRC) algorithm is the engine that enables this feature, and it leverages information on 22 million citations. We analyzed the performance of the PRC algorithm on 4584 annotated articles from the 2005 Text REtrieval Conference (TREC) Genomics Track data. Our analysis indicated that the PRC highest weighted term was not always consistent with the critical term that was most directly related to the topic of the article...
2016: AMIA Summits on Translational Science Proceedings
Nicole A Restrepo, Eric Farber-Eger, Dana C Crawford
A hurdle to EMR-based studies is the characterization and extraction of complex phenotypes not readily defined by single diagnostic/procedural codes. Here we developed an algorithm utilizing data mining techniques to identify a diabetic retinopathy (DR) cohort of type-2 diabetic African Americans from the Vanderbilt University de-identified EMR system. The algorithm incorporates a combination of diagnostic codes, current procedural terminology billing codes, medications, and text matching to identify DR when gold-standard digital photography results were unavailable...
2016: AMIA Summits on Translational Science Proceedings
Lichang Wang, Yong Fang, Dima Aref, Suyash Rathi, Li Shen, Xiaoqian Jiang, Shuang Wang
PAtients Like My gEnome (PALME) is a webservice that matches patients based on their genome and healthcare profiles. We support two types of inputs: (1) dual query (a variant + phenotype), and (2) genome sequences. For the first type of queries, we will show the patient profile matching the inputs. For the second type of queries, we will calculate similarity (based on Hamming distance) and show the distribution of phenotypes of similar patients given the input sequences of a target patient. Using the publicly available Personal Genome Project (PGP) dataset, we retrieved 4,360 patients' profiles along with their genome data, medical conditions, and treatments...
2016: AMIA Summits on Translational Science Proceedings
Douglas Redd, Jinqiu Kuang, April Mohanty, Bruce E Bray, Qing Zeng-Treitler
Functional status as measured by exercise capacity is an important clinical variable in the care of patients with cardiovascular diseases. Exercise capacity is commonly reported in terms of Metabolic Equivalents (METs). In the medical records, METs can often be found in a variety of clinical notes. To extract METs values, we adapted a machine-learning algorithm called REDEx to automatically generate regular expressions. Trained and tested on a set of 2701 manually annotated text snippets (i.e. short pieces of text), the regular expressions were able to achieve good accuracy and F-measure of 0...
2016: AMIA Summits on Translational Science Proceedings
Joseph D Romano, Nicholas P Tatonetti
Venoms and venom-derived compounds constitute a rich and largely unexplored source of potentially therapeutic compounds. To facilitate biomedical research, it is necessary to design a robust informatics infrastructure that will allow semantic computation of venom concepts in a standardized, consistent manner. We have designed an ontology of venom-related concepts - named Venom Ontology - that reuses an existing public data source: UniProt's Tox-Prot database. In addition to describing the ontology and its construction, we have performed three separate case studies demonstrating its utility: (1) An exploration of venom peptide similarity networks within specific genera; (2) A broad overview of the distribution of available data among common taxonomic groups spanning the known tree of life; and (3) An analysis of the distribution of venom complexity across those same taxonomic groups...
2016: AMIA Summits on Translational Science Proceedings
Kalpana Raja, Naman Dasot, Pawan Goyal, Siddhartha R Jonnalagadda
Precision Medicine is an emerging approach for prevention and treatment of disease that considers individual variability in genes, environment, and lifestyle for each person. The dissemination of individualized evidence by automatically identifying population information in literature is a key for evidence-based precision medicine at the point-of-care. We propose a hybrid approach using natural language processing techniques to automatically extract the population information from biomedical literature. Our approach first implements a binary classifier to classify sentences with or without population information...
2016: AMIA Summits on Translational Science Proceedings
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