Connection

Co-Authors

This is a "connection" page, showing publications co-authored by Robert Lund and Christopher Mcmahan.
Connection Strength

0.686
  1. Liu Y, Watson SC, Gettings JR, Lund RB, Nordone SK, Yabsley MJ, McMahan CS. A Bayesian spatio-temporal model for forecasting Anaplasma species seroprevalence in domestic dogs within the contiguous United States. PLoS One. 2017; 12(7):e0182028.
    View in: PubMed
    Score: 0.170
  2. Liu Y, Lund RB, Nordone SK, Yabsley MJ, McMahan CS. A Bayesian spatio-temporal model for forecasting the prevalence of antibodies to Ehrlichia species in domestic dogs within the contiguous United States. Parasit Vectors. 2017 Mar 09; 10(1):138.
    View in: PubMed
    Score: 0.166
  3. Bowman DD, Liu Y, McMahan CS, Nordone SK, Yabsley MJ, Lund RB. Forecasting United States heartworm Dirofilaria immitis prevalence in dogs. Parasit Vectors. 2016 10 10; 9(1):540.
    View in: PubMed
    Score: 0.161
  4. Self SCW, Liu Y, Nordone SK, Yabsley MJ, Walden HS, Lund RB, Bowman DD, Carpenter C, McMahan CS, Gettings JR. Canine vector-borne disease: mapping and the accuracy of forecasting using big data from the veterinary community. Anim Health Res Rev. 2019 06; 20(1):47-60.
    View in: PubMed
    Score: 0.050
  5. Orr RK, Hoehn JL, Col NF. The learning curve for sentinel node biopsy in breast cancer: practical considerations. Arch Surg. 1999 Jul; 134(7):764-7.
    View in: PubMed
    Score: 0.049
  6. Liu Y, Nordone SK, Yabsley MJ, Lund RB, McMahan CS, Gettings JR. Quantifying the relationship between human Lyme disease and Borrelia burgdorferi exposure in domestic dogs. Geospat Health. 2019 05 14; 14(1).
    View in: PubMed
    Score: 0.048
  7. Watson SC, Liu Y, Lund RB, Gettings JR, Nordone SK, McMahan CS, Yabsley MJ. A Bayesian spatio-temporal model for forecasting the prevalence of antibodies to Borrelia burgdorferi, causative agent of Lyme disease, in domestic dogs within the contiguous United States. PLoS One. 2017; 12(5):e0174428.
    View in: PubMed
    Score: 0.042
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.