First Header Logo Second Header Logo

Connection

Ryan Maves to Phenotype

This is a "connection" page, showing publications Ryan Maves has written about Phenotype.
Connection Strength

0.093
  1. Epsi NJ, Powers JH, Lindholm DA, Mende K, Malloy A, Ganesan A, Huprikar N, Lalani T, Smith A, Mody RM, Jones MU, Bazan SE, Colombo RE, Colombo CJ, Ewers EC, Larson DT, Berjohn CM, Maldonado CJ, Blair PW, Chenoweth J, Saunders DL, Livezey J, Maves RC, Sanchez Edwards M, Rozman JS, Simons MP, Tribble DR, Agan BK, Burgess TH, Pollett SD. A machine learning approach identifies distinct early-symptom cluster phenotypes which correlate with hospitalization, failure to return to activities, and prolonged COVID-19 symptoms. PLoS One. 2023; 18(2):e0281272.
    View in: PubMed
    Score: 0.047
  2. Blair PW, Brandsma J, Chenoweth J, Richard SA, Epsi NJ, Mehta R, Striegel D, Clemens EG, Alharthi S, Lindholm DA, Maves RC, Larson DT, Mende K, Colombo RE, Ganesan A, Lalani T, Colombo CJ, Malloy AA, Snow AL, Schully KL, Lanteri C, Simons MP, Dumler JS, Tribble D, Burgess T, Pollett S, Agan BK, Clark DV. Distinct blood inflammatory biomarker clusters stratify host phenotypes during the middle phase of COVID-19. Sci Rep. 2022 Dec 28; 12(1):22471.
    View in: PubMed
    Score: 0.046
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.