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https://www.readbyqxmd.com/read/28816837/individualizing-thresholds-of-cerebral-perfusion-pressure-using-estimated-limits-of-autoregulation
#1
Joseph Donnelly, Marek Czosnyka, Hadie Adams, Chiara Robba, Luzius A Steiner, Danilo Cardim, Brenno Cabella, Xiuyun Liu, Ari Ercole, Peter John Hutchinson, David Krishna Menon, Marcel J H Aries, Peter Smielewski
OBJECTIVES: In severe traumatic brain injury, cerebral perfusion pressure management based on cerebrovascular pressure reactivity index has the potential to provide a personalized treatment target to improve patient outcomes. So far, the methods have focused on identifying "one" autoregulation-guided cerebral perfusion pressure target-called "cerebral perfusion pressure optimal". We investigated whether a cerebral perfusion pressure autoregulation range-which uses a continuous estimation of the "lower" and "upper" cerebral perfusion pressure limits of cerebrovascular pressure autoregulation (assessed with pressure reactivity index)-has prognostic value...
September 2017: Critical Care Medicine
https://www.readbyqxmd.com/read/28816670/colorization-using-neural-network-ensemble
#2
Zezhou Cheng, Qingxiong Yang, Bin Sheng
This paper investigates into the colorization problem which converts a grayscale image to a colorful version. This is a difficult problem and normally requires manual adjustment to achieve artifact-free quality. For instance, it normally requires human-labelled color scribbles on the grayscale target image or a careful selection of colorful reference images. The recent learning-based colorization techniques automatically colorize a grayscale image using a single neural network. Since different scenes usually have distinct color styles, it is difficult to accurately capture the color characteristics using a single neural network...
August 16, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28816473/the-effects-of-context-on-processing-words-during-sentence-reading-among-adults-varying-in-age-and-literacy-skill
#3
Allison A Steen-Baker, Shukhan Ng, Brennan R Payne, Carolyn J Anderson, Kara D Federmeier, Elizabeth A L Stine-Morrow
The facilitation of word processing by sentence context reflects the interaction between the build-up of message-level semantics and lexical processing. Yet, little is known about how this effect varies through adulthood as a function of reading skill. In this study, Participants 18-64 years old with a range of literacy competence read simple sentences as their eye movements were monitored. We manipulated the predictability of a sentence-final target word, operationalized as cloze probability. First fixation durations showed an interaction between age and literacy skill, decreasing with age among more skilled readers but increasing among less skilled readers...
August 2017: Psychology and Aging
https://www.readbyqxmd.com/read/28816292/-precision-of-three-dimensional-printed-brackets
#4
D Zhang, L C Wang, Y H Zhou, X M Liu, J Li
OBJECTIVE: This study was based on digital orthodontic diagnosis work flow for indirect bonding transfer tray model design and three-dimensional (3D) printing, and the aim of this paper was to inspect the dimensional accuracyof 3D printed brackets, which is the foundation of the follow up work and hoped that will illuminate the clinical application of the digital orthodontics work flow. METHODS: The samples which consisted of 14 cases of patients with malocclusion from Department of Orthodontics Peking University were selected, including 8 cases with tooth extraction and 6 cases without tooth extraction...
August 18, 2017: Beijing da Xue Xue Bao. Yi Xue Ban, Journal of Peking University. Health Sciences
https://www.readbyqxmd.com/read/28816207/evaluation-of-the-effects-of-various-sound-pressure-levels-on-the-level-of-serum-aldosterone-concentration-in-rats
#5
Parvin Nassiri, Sajad Zare, Mohammad R Monazzam, Akram Pourbakht, Kamal Azam, Taghi Golmohammadi
INTRODUCTION: Noise exposure may have anatomical, nonauditory, and auditory influences. Considering nonauditory impacts, noise exposure can cause alterations in the automatic nervous system, including increased pulse rates, heightened blood pressure, and abnormal secretion of hormones. The present study aimed at examining the effect of various sound pressure levels (SPLs) on the serum aldosterone level among rats. MATERIALS AND METHODS: A total of 45 adult male rats with an age range of 3 to 4 months and a weight of 200 ± 50 g were randomly divided into 15 groups of three...
July 2017: Noise & Health
https://www.readbyqxmd.com/read/28815723/rapid-automatic-creation-of-monodisperse-emulsion-droplets-by-microfluidic-device-with-degassed-pdms-slab-as-a-detachable-suction-actuator
#6
Yuki Murata, Yuta Nakashoji, Masaki Kondo, Yugo Tanaka, Masahiko Hashimoto
We previously developed a technique that enabled automatic creation of monodisperse water-in-oil droplets with the use of an air-evacuated PDMS microfluidic device. Although the device generated droplets over a long-time period, the production rate was slow (∼10 droplets per second). In the current study, we aimed to improve this rate, using the same fluid pumping principle described in our previous work, by remodeling our device configuration. To achieve this aim, we developed a new device with a much larger PDMS surface area-to-volume ratio within the air-trapping void space (178 cm(-1) ), than that of our earlier device (5...
August 16, 2017: Electrophoresis
https://www.readbyqxmd.com/read/28815472/comparison-of-pet-ct-and-whole-mount-histopathology-sections-of-the-human-prostate-a-new-strategy-for-voxel-wise-evaluation
#7
F Schiller, T Fechter, C Zamboglou, A Chirindel, N Salman, C A Jilg, V Drendel, M Werner, P T Meyer, A-L Grosu, M Mix
BACKGROUND: Implementation of PET/CT in diagnosis of primary prostate cancer (PCa) requires a profound knowledge about the tracer, preferably from a quantitative evaluation. Direct visual comparison of PET/CT slices to whole prostate sections is hampered by considerable uncertainties from imperfect coregistration and fundamentally different image modalities. In the current study, we present a novel method for advanced voxel-wise comparison of histopathology from excised prostates to pre-surgical PET...
August 17, 2017: EJNMMI Physics
https://www.readbyqxmd.com/read/28815426/identification-and-red-blood-cell-automated-counting-from-blood-smear-images-using-computer-aided-system
#8
Vasundhara Acharya, Preetham Kumar
Red blood cell count plays a vital role in identifying the overall health of the patient. Hospitals use the hemocytometer to count the blood cells. Conventional method of placing the smear under microscope and counting the cells manually lead to erroneous results, and medical laboratory technicians are put under stress. A computer-aided system will help to attain precise results in less amount of time. This research work proposes an image-processing technique for counting the number of red blood cells. It aims to examine and process the blood smear image, in order to support the counting of red blood cells and identify the number of normal and abnormal cells in the image automatically...
August 17, 2017: Medical & Biological Engineering & Computing
https://www.readbyqxmd.com/read/28815362/metric-to-quantify-white-matter-damage-on-brain-magnetic-resonance-images
#9
Maria Del C Valdés Hernández, Francesca M Chappell, Susana Muñoz Maniega, David Alexander Dickie, Natalie A Royle, Zoe Morris, Devasuda Anblagan, Eleni Sakka, Paul A Armitage, Mark E Bastin, Ian J Deary, Joanna M Wardlaw
PURPOSE: Quantitative assessment of white matter hyperintensities (WMH) on structural Magnetic Resonance Imaging (MRI) is challenging. It is important to harmonise results from different software tools considering not only the volume but also the signal intensity. Here we propose and evaluate a metric of white matter (WM) damage that addresses this need. METHODS: We obtained WMH and normal-appearing white matter (NAWM) volumes from brain structural MRI from community dwelling older individuals and stroke patients enrolled in three different studies, using two automatic methods followed by manual editing by two to four observers blind to each other...
August 16, 2017: Neuroradiology
https://www.readbyqxmd.com/read/28815151/eye-tracking-for-clinical-decision-support-a-method-to-capture-automatically-what-physicians-are-viewing-in-the-emr
#10
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/28815149/classifying-supplement-use-status-in-clinical-notes
#11
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/28815137/combining-kernel-and-model-based-learning-for-hiv-therapy-selection
#12
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/28815135/active-deep-learning-based-annotation-of-electroencephalography-reports-for-cohort-identification
#13
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/28815129/sdt-a-tree-method-for-detecting-patient-subgroups-with-personalized-risk-factors
#14
Xiangrui Li, Dongxiao Zhu, Ming Dong, Milad Zafar Nezhad, Alexander Janke, Phillip D Levy
Eradicating health disparity is a new focus for precision medicine research. Identifying patient subgroups is an effective approach to customized treatments for maximizing efficiency in precision medicine. Some features may be important risk factors for specific patient subgroups but not necessarily for others, resulting in a potential divergence in treatments designed for a given population. In this paper, we propose a tree-based method, called Subgroup Detection Tree (SDT), to detect patient subgroups with personalized risk factors...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815128/a-comparative-study-of-different-methods-for-automatic-identification-of-clopidogrel-induced-bleedings-in-electronic-health-records
#15
Hee-Jin Lee, Min Jiang, Yonghui Wu, Christian M Shaffer, John H Cleator, Eitan A Friedman, Joshua P Lewis, Dan M Roden, Josh Denny, Hua Xu
Electronic health records (EHRs) linked with biobanks have been recognized as valuable data sources for pharmacogenomic studies, which require identification of patients with certain adverse drug reactions (ADRs) from a large population. Since manual chart review is costly and time-consuming, automatic methods to accurately identify patients with ADRs have been called for. In this study, we developed and compared different informatics approaches to identify ADRs from EHRs, using clopidogrel-induced bleeding as our case study...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815127/a-knowledge-based-system-for-intelligent-support-in-pharmacogenomics-evidence-assessment-ontology-driven-evidence-representation-and-retrieval
#16
Chia-Ju Lee, Beth Devine, Peter Tarczy-Hornoch
Pharmacogenomics holds promise as a critical component of precision medicine. Yet, the use of pharmacogenomics in routine clinical care is minimal, partly due to the lack of efficient and effective use of existing evidence. This paper describes the design, development, implementation and evaluation of a knowledge-based system that fulfills three critical features: a) providing clinically relevant evidence, b) applying an evidence-based approach, and c) using semantically computable formalism, to facilitate efficient evidence assessment to support timely decisions on adoption of pharmacogenomics in clinical care...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815124/pheknow-cloud-a-tool-for-evaluating-high-throughput-phenotype-candidates-using-online-medical-literature
#17
Jette Henderson, Ryan Bridges, Joyce C Ho, Byron C Wallace, Joydeep Ghosh
As the adoption of Electronic Healthcare Records has grown, the need to transform manual processes that extract and characterize medical data into automatic and high-throughput processes has also grown. Recently, researchers have tackled the problem of automatically extracting candidate phenotypes from EHR data. Since these phenotypes are usually generated using unsupervised or semi-supervised methods, it is necessary to examine and validate the clinical relevance of the generated "candidate" phenotypes. We present PheKnow-Cloud, a framework that uses co-occurrence analysis on the publicly available, online repository ofjournal articles, PubMed, to build sets of evidence for user-supplied candidate phenotypes...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815119/extracting-geographic-locations-from-the-literature-for-virus-phylogeography-using-supervised-and-distant-supervision-methods
#18
Davy Weissenbacher, Abeed Sarker, Tasnia Tahsin, Matthew Scotch, Graciela Gonzalez
The field of phylogeography allows researchers to model the spread and evolution of viral genetic sequences. Phylogeography plays a major role in infectious disease surveillance, viral epidemiology and vaccine design. When conducting viral phylogeographic studies, researchers require the location of the infected host of the virus, which is often present in public databases such as GenBank. However, the geographic metadata in most GenBank records is not precise enough for many phylogeographic studies; therefore, researchers often need to search the articles linked to the records for more information, which can be a tedious process...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815118/deep-learning-from-eeg-reports-for-inferring-underspecified-information
#19
Travis R Goodwin, Sanda M Harabagiu
Secondary use(1)of electronic health records (EHRs) often relies on the ability to automatically identify and extract information from EHRs. Unfortunately, EHRs are known to suffer from a variety of idiosyncrasies - most prevalently, they have been shown to often omit or underspecify information. Adapting traditional machine learning methods for inferring underspecified information relies on manually specifying features characterizing the specific information to recover (e.g. particular findings, test results, or physician's impressions)...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815103/search-datasets-in-literature-a-case-study-of-gwas
#20
Xiao Dong, Yaoyun Zhang, Hua Xu
One of the missions of the NIH BD2K (Big Data to Knowledge) initiative is to make data discoverable and promote the re-use of existing datasets. Our ultimate goal is to develop a scalable approach that can automatically scan millions of scientific publications and identify underlying data sets. Using Genome-Wide Association Studies (GWAS) as a use case, we conducted an initial study to identify GWAS dataset attributes in MEDLINE abstracts, by developing a hybrid approach that combines domain dictionaries and pattern-based rules...
2017: AMIA Summits on Translational Science Proceedings
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