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  1. Article ; Online: COVID-19 Exposure Risk by Speakers of Spanish and English Using a Web-Based Self-assessment Tool.

    Mehring, William M / Kim, Jeniffer S / Hendel, Chris / Hochman, Michael

    Journal of general internal medicine

    2021  Volume 36, Issue 6, Page(s) 1835–1836

    MeSH term(s) COVID-19 ; Ethnicity ; Humans ; Internet ; Multilingualism ; SARS-CoV-2 ; Self-Assessment ; United States
    Language English
    Publishing date 2021-04-05
    Publishing country United States
    Document type Letter ; Comment
    ZDB-ID 639008-0
    ISSN 1525-1497 ; 0884-8734
    ISSN (online) 1525-1497
    ISSN 0884-8734
    DOI 10.1007/s11606-021-06756-y
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 2205: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  2. Article ; Online: Initial Experience with a COVID-19 Web-Based Patient Self-assessment Tool.

    Mehring, William M / Poksay, Andrew / Kriege, Jesse / Prasannappa, Rithvik / Wang, Michael D / Hendel, Chris / Hochman, Michael

    Journal of general internal medicine

    2020  Volume 35, Issue 9, Page(s) 2821–2822

    MeSH term(s) Adult ; Betacoronavirus ; COVID-19 ; Coronavirus Infections/diagnosis ; Coronavirus Infections/epidemiology ; Coronavirus Infections/psychology ; Female ; Humans ; Internet/trends ; Male ; Pandemics ; Pneumonia, Viral/diagnosis ; Pneumonia, Viral/epidemiology ; Pneumonia, Viral/psychology ; SARS-CoV-2 ; Self-Assessment
    Keywords covid19
    Language English
    Publishing date 2020-06-15
    Publishing country United States
    Document type Letter
    ZDB-ID 639008-0
    ISSN 1525-1497 ; 0884-8734
    ISSN (online) 1525-1497
    ISSN 0884-8734
    DOI 10.1007/s11606-020-05893-0
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 2205: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  3. Article: Initial Experience with a COVID-19 Web-Based Patient Self-assessment Tool

    Mehring, William M / Poksay, Andrew / Kriege, Jesse / Prasannappa, Rithvik / Wang, Michael D / Hendel, Chris / Hochman, Michael

    J Gen Intern Med

    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #598902
    Database COVID19

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  4. Article ; Online: Initial Experience with a COVID-19 Web-Based Patient Self-assessment Tool

    Mehring, William M. / Poksay, Andrew / Kriege, Jesse / Prasannappa, Rithvik / Wang, Michael D. / Hendel, Chris / Hochman, Michael

    Journal of General Internal Medicine

    2020  Volume 35, Issue 9, Page(s) 2821–2822

    Keywords Internal Medicine ; covid19
    Language English
    Publisher Springer Science and Business Media LLC
    Publishing country us
    Document type Article ; Online
    ZDB-ID 639008-0
    ISSN 1525-1497 ; 0884-8734
    ISSN (online) 1525-1497
    ISSN 0884-8734
    DOI 10.1007/s11606-020-05893-0
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 2205: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  5. Article ; Online: A new open-access platform for measuring and sharing mTBI data.

    Domel, August G / Raymond, Samuel J / Giordano, Chiara / Liu, Yuzhe / Yousefsani, Seyed Abdolmajid / Fanton, Michael / Cecchi, Nicholas J / Vovk, Olga / Pirozzi, Ileana / Kight, Ali / Avery, Brett / Boumis, Athanasia / Fetters, Tyler / Jandu, Simran / Mehring, William M / Monga, Sam / Mouchawar, Nicole / Rangel, India / Rice, Eli /
    Roy, Pritha / Sami, Sohrab / Singh, Heer / Wu, Lyndia / Kuo, Calvin / Zeineh, Michael / Grant, Gerald / Camarillo, David B

    Scientific reports

    2021  Volume 11, Issue 1, Page(s) 7501

    Abstract: Despite numerous research efforts, the precise mechanisms of concussion have yet to be fully uncovered. Clinical studies on high-risk populations, such as contact sports athletes, have become more common and give insight on the link between impact ... ...

    Abstract Despite numerous research efforts, the precise mechanisms of concussion have yet to be fully uncovered. Clinical studies on high-risk populations, such as contact sports athletes, have become more common and give insight on the link between impact severity and brain injury risk through the use of wearable sensors and neurological testing. However, as the number of institutions operating these studies grows, there is a growing need for a platform to share these data to facilitate our understanding of concussion mechanisms and aid in the development of suitable diagnostic tools. To that end, this paper puts forth two contributions: (1) a centralized, open-access platform for storing and sharing head impact data, in collaboration with the Federal Interagency Traumatic Brain Injury Research informatics system (FITBIR), and (2) a deep learning impact detection algorithm (MiGNet) to differentiate between true head impacts and false positives for the previously biomechanically validated instrumented mouthguard sensor (MiG2.0), all of which easily interfaces with FITBIR. We report 96% accuracy using MiGNet, based on a neural network model, improving on previous work based on Support Vector Machines achieving 91% accuracy, on an out of sample dataset of high school and collegiate football head impacts. The integrated MiG2.0 and FITBIR system serve as a collaborative research tool to be disseminated across multiple institutions towards creating a standardized dataset for furthering the knowledge of concussion biomechanics.
    MeSH term(s) Access to Information ; Algorithms ; Brain Injuries, Traumatic/diagnosis ; Humans ; Information Dissemination ; Mouth Protectors ; Neural Networks, Computer ; Reproducibility of Results ; Support Vector Machine
    Language English
    Publishing date 2021-04-05
    Publishing country England
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-021-87085-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: A new open-access platform for measuring and sharing mTBI data

    August G. Domel / Samuel J. Raymond / Chiara Giordano / Yuzhe Liu / Seyed Abdolmajid Yousefsani / Michael Fanton / Nicholas J. Cecchi / Olga Vovk / Ileana Pirozzi / Ali Kight / Brett Avery / Athanasia Boumis / Tyler Fetters / Simran Jandu / William M. Mehring / Sam Monga / Nicole Mouchawar / India Rangel / Eli Rice /
    Pritha Roy / Sohrab Sami / Heer Singh / Lyndia Wu / Calvin Kuo / Michael Zeineh / Gerald Grant / David B. Camarillo

    Scientific Reports, Vol 11, Iss 1, Pp 1-

    2021  Volume 10

    Abstract: Abstract Despite numerous research efforts, the precise mechanisms of concussion have yet to be fully uncovered. Clinical studies on high-risk populations, such as contact sports athletes, have become more common and give insight on the link between ... ...

    Abstract Abstract Despite numerous research efforts, the precise mechanisms of concussion have yet to be fully uncovered. Clinical studies on high-risk populations, such as contact sports athletes, have become more common and give insight on the link between impact severity and brain injury risk through the use of wearable sensors and neurological testing. However, as the number of institutions operating these studies grows, there is a growing need for a platform to share these data to facilitate our understanding of concussion mechanisms and aid in the development of suitable diagnostic tools. To that end, this paper puts forth two contributions: (1) a centralized, open-access platform for storing and sharing head impact data, in collaboration with the Federal Interagency Traumatic Brain Injury Research informatics system (FITBIR), and (2) a deep learning impact detection algorithm (MiGNet) to differentiate between true head impacts and false positives for the previously biomechanically validated instrumented mouthguard sensor (MiG2.0), all of which easily interfaces with FITBIR. We report 96% accuracy using MiGNet, based on a neural network model, improving on previous work based on Support Vector Machines achieving 91% accuracy, on an out of sample dataset of high school and collegiate football head impacts. The integrated MiG2.0 and FITBIR system serve as a collaborative research tool to be disseminated across multiple institutions towards creating a standardized dataset for furthering the knowledge of concussion biomechanics.
    Keywords Medicine ; R ; Science ; Q
    Subject code 306
    Language English
    Publishing date 2021-04-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Book ; Online: A New Open-Access Platform for Measuring and Sharing mTBI Data

    Domel, August G. / Raymond, Samuel J. / Giordano, Chiara / Liu, Yuzhe / Yousefsani, Seyed Abdolmajid / Fanton, Michael / Pirozzi, Ileana / Kight, Ali / Avery, Brett / Boumis, Athanasia / Fetters, Tyler / Jandu, Simran / Mehring, William M / Monga, Sam / Mouchawar, Nicole / Rangel, India / Rice, Eli / Roy, Pritha / Sami, Sohrab /
    Singh, Heer / Wu, Lyndia / Kuo, Calvin / Zeineh, Michael / Grant, Gerald / Camarillo, David B.

    2020  

    Abstract: Despite numerous research efforts, the precise mechanisms of concussion have yet to be fully uncovered. Clinical studies on high-risk populations, such as contact sports athletes, have become more common and give insight on the link between impact ... ...

    Abstract Despite numerous research efforts, the precise mechanisms of concussion have yet to be fully uncovered. Clinical studies on high-risk populations, such as contact sports athletes, have become more common and give insight on the link between impact severity and brain injury risk through the use of wearable sensors and neurological testing. However, as the number of institutions operating these studies grows, there is a growing need for a platform to share these data to facilitate our understanding of concussion mechanisms and aid in the development of suitable diagnostic tools. To that end, this paper puts forth two contributions: 1) a centralized, open-source platform for storing and sharing head impact data, in collaboration with the Federal Interagency Traumatic Brain Injury Research informatics system (FITBIR), and 2) a deep learning impact detection algorithm (MiGNet) to differentiate between true head impacts and false positives for the previously biomechanically validated instrumented mouthguard sensor (MiG2.0), all of which easily interfaces with FITBIR. We report 96% accuracy using MiGNet, based on a neural network model, improving on previous work based on Support Vector Machines achieving 91% accuracy, on an out of sample dataset of high school and collegiate football head impacts. The integrated MiG2.0 and FITBIR system serve as a collaborative research tool to be disseminated across multiple institutions towards creating a standardized dataset for furthering the knowledge of concussion biomechanics.

    Comment: 21 pages, 3 figures, 1 table
    Keywords Computer Science - Machine Learning ; Computer Science - Computers and Society ; 68T07
    Subject code 306
    Publishing date 2020-10-16
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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  8. Book: Effects of particle size on the properties and efficiency of fertilizers

    Mehring, A. L / White, L. M / Ross, William Horace / Adams, J. E

    (Technical bulletin / United States Department of Agriculture ; no. 485)

    1935  

    Institution United States. / Department of Agriculture,
    Author's details by A.L. Mehring [and others]
    Series title Technical bulletin / United States Department of Agriculture ; no. 485
    Keywords Fertilizers.
    Language English
    Size 27 pages :, illustrations ;, 23 cm.
    Publisher United States Department of Agriculture
    Publishing place Washington, D.C
    Document type Book
    Note Caption title. ; Issued September 1935.
    Database NAL-Catalogue (AGRICOLA)

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