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IEEE-EMBS International Conference on Biomedical and Health Informatics

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https://www.readbyqxmd.com/read/29862383/a-social-cognitive-theory-based-framework-for-monitoring-medication-adherence-applied-to-endocrine-therapy-in-breast-cancer-survivors
#1
Mehdi Boukhechba, Sonia Baee, Alicia L Nobles, Jiaqi Gong, Kristen Wells, Laura E Barnes
Poor adherence to long-term therapies for chronic diseases, such as cancer, compromises effectiveness of treatment and increases the likelihood of disease progression, making medication adherence a critical issue in population health. While the field has documented many eers to adherence to medication, it has also come up with few efficacious solutions to medication adherence, indicating that new and innovative approaches are needed. In this paper, we evaluate medication-taking behaviors based on social cognitive theory (SCT), presenting patterns of adherence stratified across SCT constructs in 33 breast cancer survivors over an 8-month period...
March 2018: IEEE-EMBS International Conference on Biomedical and Health Informatics
https://www.readbyqxmd.com/read/29780972/a-general-method-for-predicting-amino-acid-residues-experiencing-hydrogen-exchange
#2
Boshen Wang, Alan Perez-Rathke, Renhao Li, Jie Liang
Information on protein hydrogen exchange can help delineate key regions involved in protein-protein interactions and provides important insight towards determining functional roles of genetic variants and their possible mechanisms in disease processes. Previous studies have shown that the degree of hydrogen exchange is affected by hydrogen bond formations, solvent accessibility, proximity to other residues, and experimental conditions. However, a general predictive method for identifying residues capable of hydrogen exchange transferable to a broad set of proteins is lacking...
March 2018: IEEE-EMBS International Conference on Biomedical and Health Informatics
https://www.readbyqxmd.com/read/29938711/multimodal-ambulatory-sleep-detection
#3
Weixuan Chen, Akane Sano, Daniel Lopez Martinez, Sara Taylor, Andrew W McHill, Andrew J K Phillips, Laura Barger, Elizabeth B Klerman, Rosalind W Picard
Inadequate sleep affects health in multiple ways. Unobtrusive ambulatory methods to monitor long-term sleep patterns in large populations could be useful for health and policy decisions. This paper presents an algorithm that uses multimodal data from smartphones and wearable technologies to detect sleep/wake state and sleep episode on/offset. We collected 5580 days of multimodal data and applied recurrent neural networks for sleep/wake classification, followed by cross-correlation-based template matching for sleep episode on/offset detection...
February 2017: IEEE-EMBS International Conference on Biomedical and Health Informatics
https://www.readbyqxmd.com/read/29707698/analyzing-the-usage-of-standards-in-radiation-therapy-clinical-studies
#4
Y Zhen, Y Jiang, L Yuan, J Kirkpartrick, J Wu, Y Ge
Standards for scoring adverse effects after radiation therapy (RT) is crucial for integrated, consistent, and accurate analysis of toxicity results at large scale and across multiple studies. This project aims to investigate the usage of the three most commonly used standards in published RT clinical studies by developing a text-mining based analysis method. We develop and compare two text-mining methods, one based on regular expressions and one based on Naïve Bayes Classifier, to analyze published full articles in terms of their adoption of standards in RT...
February 2017: IEEE-EMBS International Conference on Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28804791/intelligent-mortality-reporting-with-fhir
#5
Ryan A Hoffman, Hang Wu, Janani Venugopalan, Paula Braun, May D Wang
One pressing need in the area of public health is timely, accurate, and complete reporting of deaths and the conditions leading up to them. Fast Healthcare Interoperability Resources (FHIR) is a new HL7 interoperability standard for electronic health record (EHR), while Sustainable Medical Applications and Reusable Technologies (SMART)-on-FHIR enables third-party app development that can work "out of the box". This research demonstrates the feasibility of developing SMART-on-FHIR applications to enable medical professionals to perform timely and accurate death reporting within multiple different jurisdictions of US...
February 2017: IEEE-EMBS International Conference on Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28736772/on-quantifying-diffusion-of-health-information-on-twitter
#6
Gokhan Bakal, Ramakanth Kavuluru
With the increasing use of digital technologies, online social networks are emerging as major means of communication. Recently, social networks such as Facebook and Twitter are also being used by consumers, care providers (physicians, hospitals), and government agencies to share health related information. The asymmetric user network and the short message size have made Twitter particularly popular for propagating health related content on the Web. Besides tweeting on their own, users can choose to retweet particular tweets from other users (even if they do not follow them on Twitter...
February 2017: IEEE-EMBS International Conference on Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28725879/using-closure-tables-to-enable-cross-querying-of-ontologies-in-database-driven-applications
#7
Daniel R Harris, Darren W Henderson, Jeffery C Talbert
We demonstrate that closure tables are an effective data structure for developing database-driven applications that query biomedical ontologies and that require cross-querying between multiple ontologies. A closure table stores all available paths within a tree, even those without a direct parent-child relationship; additionally, a node can have multiple ancestors which gives the foundation for supporting linkages between controlled ontologies. We augment the meta-data structure of the ICD9 and ICD10 ontologies included in i2b2, an open source query tool for identifying patient cohorts, to utilize a closure table...
February 2017: IEEE-EMBS International Conference on Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28630952/estimating-patient-s-health-state-using-latent-structure-inferred-from-clinical-time-series-and-text
#8
Aaron Zalewski, William Long, Alistair E W Johnson, Roger G Mark, Li-Wei H Lehman
Modern intensive care units (ICUs) collect large volumes of data in monitoring critically ill patients. Clinicians in the ICUs face the challenge of interpreting large volumes of high-dimensional data to diagnose and treat patients. In this work, we explore the use of Hierarchical Dirichlet Processes (HDP) as a Bayesian nonparametric framework to infer patients' states of health by combining multiple sources of data. In particular, we employ HDP to combine clinical time series and text from the nursing progress notes in a probabilistic topic modeling framework for patient risk stratification...
February 2017: IEEE-EMBS International Conference on Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28630951/phenotyping-hypotensive-patients-in-critical-care-using-hospital-discharge-summaries
#9
Yang Dai, Sharukh Lokhandwala, William Long, Roger Mark, Li-Wei H Lehman
Among critically-ill patients, hypotension represents a failure in compensatory mechanisms and may lead to organ hypoperfusion and failure. In this work, we adopt a data-driven approach for phenotype discovery and visualization of patient similarity and cohort structure in the intensive care unit (ICU). We used Hierarchical Dirichlet Process (HDP) as a nonparametric topic modeling technique to automatically learn a d-dimensional feature representation of patients that captures the latent "topic" structure of diseases, symptoms, medications, and findings documented in hospital discharge summaries...
February 2017: IEEE-EMBS International Conference on Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28580455/detection-of-nuclei-in-h-e-stained-sections-using-convolutional-neural-networks
#10
Mina Khoshdeli, Richard Cong, Bahram Parvin
Detection of nuclei is an important step in phenotypic profiling of histology sections that are usually imaged in bright field. However, nuclei can have multiple phenotypes, which are difficult to model. It is shown that convolutional neural networks (CNN)s can learn different phenotypic signatures for nuclear detection, and that the performance is improved with the feature-based representation of the original image. The feature-based representation utilizes Laplacian of Gaussian (LoG) filter, which accentuates blob-shape objects...
February 2017: IEEE-EMBS International Conference on Biomedical and Health Informatics
https://www.readbyqxmd.com/read/29750222/agile-model-driven-development-of-electronic-health-record-based-specialty-population-registries
#11
Vaishnavi Kannan, Jason C Fish, DuWayne L Willett
The transformation of the American healthcare payment system from fee-for-service to value-based care increasingly makes it valuable to develop patient registries for specialized populations, to better assess healthcare quality and costs. Recent widespread adoption of Electronic Health Records (EHRs) in the U.S. now makes possible construction of EHR-based specialty registry data collection tools and reports, previously unfeasible using manual chart abstraction. But the complexities of specialty registry EHR tools and measures, along with the variety of stakeholders involved, can result in misunderstood requirements and frequent product change requests, as users first experience the tools in their actual clinical workflows...
February 2016: IEEE-EMBS International Conference on Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28721401/toward-patient-tailored-summarization-of-lung-cancer-literature
#12
Jean I Garcia-Gathright, Nicholas J Matiasz, Edward B Garon, Denise R Aberle, Ricky K Taira, Alex A T Bui
As the volume of biomedical literature increases, it can be challenging for clinicians to stay up-to-date. Graphical summarization systems help by condensing knowledge into networks of entities and relations. However, existing systems present relations out of context, ignoring key details such as study population. To better support precision medicine, summarization systems should include such information to contextualize and tailor results to individual patients. This paper introduces "contextualized semantic maps" for patient-tailored graphical summarization of published literature...
February 2016: IEEE-EMBS International Conference on Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28702513/an-auditory-nerve-stimulation-chip-with-integrated-afe-sound-processing-and-power-management-for-fully-implantable-cochlear-implants
#13
Nijad Anabtawi, Sabrina Freeman, Rony Ferzli
This paper presents a system on chip for a fully implantable cochlear implant. It includes acoustic sensor front-end, 4-channel digital sound processing and auditory nerve stimulation circuitry. It also features a digital, switched mode, single inductor dual output power supply that generates two regulated voltages; 0.4 V used to supply on-chip digital blocks and 0.9 V to supply analog blocks and charge the battery when an external RF source is detected. All passives are integrated on-chip including the inductor...
February 2016: IEEE-EMBS International Conference on Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28702512/a-fully-implantable-nfc-enabled-continuous-interstitial-glucose-monitor
#14
Nijad Anabtawi, Sabrina Freeman, Rony Ferzli
This work presents an integrated system-on-chip (SoC) that forms the core of a long-term, fully implantable, battery assisted, passive continuous glucose monitor. It integrates an amperometric glucose sensor interface, a near field communication (NFC) wireless front-end and a fully digital switched mode power management unit for supply regulation and on board battery charging. It uses 13.56 MHz (ISM) band to harvest energy and backscatter data to an NFC reader. System was implemented in 14nm CMOS technology and validated with post layout simulations...
February 2016: IEEE-EMBS International Conference on Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28670648/assessing-variability-in-brain-tumor-segmentation-to-improve-volumetric-accuracy-and-characterization-of-change
#15
Edgar A Rios Piedra, Ricky K Taira, Suzie El-Saden, Benjamin M Ellingson, Alex A T Bui, William Hsu
Brain tumor analysis is moving towards volumetric assessment of magnetic resonance imaging (MRI), providing a more precise description of disease progression to better inform clinical decision-making and treatment planning. While a multitude of segmentation approaches exist, inherent variability in the results of these algorithms may incorrectly indicate changes in tumor volume. In this work, we present a systematic approach to characterize variability in tumor boundaries that utilizes equivalence tests as a means to determine whether a tumor volume has significantly changed over time...
February 2016: IEEE-EMBS International Conference on Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28480454/predicting-lung-cancer-incidence-from-air-pollution-exposures-using-shapelet-based-time-series-analysis
#16
Hong-Jun Yoon, Songhua Xu, Georgia Tourassi
In this paper we investigated whether the geographical variation of lung cancer incidence can be predicted through examining the spatiotemporal trend of particulate matter air pollution levels. Regional trends of air pollution levels were analyzed by a novel shapelet-based time series analysis technique. First, we identified U.S. counties with reportedly high and low lung cancer incidence between 2008 and 2012 via the State Cancer Profiles provided by the National Cancer Institute. Then, we collected particulate matter exposure levels (PM2...
February 2016: IEEE-EMBS International Conference on Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28164175/pepcor-a-risk-prediction-model-for-pediatric-intensive-care-units-utilizing-ventilator-days-and-length-of-stay
#17
Theruni Pethiyagoda, Nikhil Chanani, Chihwen Cheng, May D Wang
Great sources of concern for pediatric and neonatal intensive care units are the total resource utilization and cost of caring for very sick children. This paper attempts to create a usable clinical decision support system (PEPCOR) that would help improve personalized health care and avoid unnecessary secondary, and costly, procedures that do not improve the care of a critically ill patient. The system uses the Children's Healthcare of Atlanta ICU database to analyze the effects on the risk, (quantified as the risk of invasive ventilation and associated complications) when combining two procedures versus administering one procedure without the other...
February 2016: IEEE-EMBS International Conference on Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28133639/informatics-based-challenges-of-building-collaborative-healthcare-research-and-analysis-networks-from-rural-community-health-centers
#18
Daniel R Harris, Tamela J Harper, Darren W Henderson, Keith W Henry, Jeffery C Talbert
We discuss informatics-based challenges of constructing large-scale collaborative networks for healthcare research and analysis from rural community health centers. These types of networks provide data access and analytic insights across multiple heterogeneous health centers for both healthcare professionals and biomedical researchers. Challenges fall into three general categories: data access, data integration, and technical infrastructure. Data access issues arise in balancing patient privacy, security, and utility; data integration issues persist from each site independently operating its desired electronic medical record; technical infrastructure challenges include creating an analysis and reporting hub capable of scaling across a large collaborative network...
February 2016: IEEE-EMBS International Conference on Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28133638/development-of-user-friendly-and-interactive-data-collection-system-for-cerebral-palsy
#19
I Raharjo, T G Burns, J Venugopalan, M D Wang
Cerebral palsy (CP) is a permanent motor disorder that appears in early age and it requires multiple tests to assess the physical and mental capabilities of the patients. Current medical record data collection systems, e.g., EPIC, employed for CP are very general, difficult to navigate, and prone to errors. The data cannot easily be extracted which limits data analysis on this rich source of information. To overcome these limitations, we designed and prototyped a database with a graphical user interface geared towards clinical research specifically in CP...
February 2016: IEEE-EMBS International Conference on Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28133637/the-selection-of-quantification-pipelines-for-illumina-rna-seq-data-using-a-subsampling-approach
#20
Po-Yen Wu, May D Wang
RNA sequencing, or (RNA-seq for short,, is a widely applied technology that for extractings gene and transcript expression from biological samples. Given numerous quantification pipelines for RNA-seq data, one fundamental challenge is to determine identify a pipeline that can produce the most accurate estimate the most accurate gene and/or transcript expression. Exploring all available pipelines requires tremendous extensive computational resources, so. Therefore, we propose to use a subsampling approach that can improve speed up the pipeline evaluation and selection the efficiency process of pipeline performance evaluation for a given RNA-seq dataset...
February 2016: IEEE-EMBS International Conference on Biomedical and Health Informatics
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