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Connection

Joseph Rigdon to Proportional Hazards Models

This is a "connection" page, showing publications Joseph Rigdon has written about Proportional Hazards Models.
Connection Strength

0.249
  1. Rigdon J, Basu S. Machine learning with sparse nutrition data to improve cardiovascular mortality risk prediction in the USA using nationally randomly sampled data. BMJ Open. 2019 11 28; 9(11):e032703.
    View in: PubMed
    Score: 0.148
  2. Saha P, Potiny P, Rigdon J, Morello M, Tcheandjieu C, Romfh A, Fernandes SM, McElhinney DB, Bernstein D, Lui GK, Shaw GM, Ingelsson E, Priest JR. Substantial Cardiovascular Morbidity in Adults With Lower-Complexity Congenital Heart Disease. Circulation. 2019 04 16; 139(16):1889-1899.
    View in: PubMed
    Score: 0.035
  3. Afghahi A, Purington N, Han SS, Desai M, Pierson E, Mathur MB, Seto T, Thompson CA, Rigdon J, Telli ML, Badve SS, Curtis CN, West RB, Horst K, Gomez SL, Ford JM, Sledge GW, Kurian AW. Higher Absolute Lymphocyte Counts Predict Lower Mortality from Early-Stage Triple-Negative Breast Cancer. Clin Cancer Res. 2018 06 15; 24(12):2851-2858.
    View in: PubMed
    Score: 0.033
  4. Basu S, Sussman JB, Rigdon J, Steimle L, Denton BT, Hayward RA. Benefit and harm of intensive blood pressure treatment: Derivation and validation of risk models using data from the SPRINT and ACCORD trials. PLoS Med. 2017 Oct; 14(10):e1002410.
    View in: PubMed
    Score: 0.032
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.