 Connection
Rasika Mathias to Machine Learning
This is a "connection" page, showing publications Rasika Mathias has written about Machine Learning.
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Connection Strength |
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0.117 |
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Williams CM, Scelza BA, Slack SD, Font-Porterias N, Al-Hindi DR, Mathias RA, Watson H, Barnes KC, Lange E, Johnson RK, Gignoux CR, Ramachandran S, Henn BM. A rapid accurate approach to inferring pedigrees in endogamous populations. Genetics. 2025 Aug 06; 230(4).
Score: 0.041
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Little A, Zhao N, Mikhaylova A, Zhang A, Ling W, Thibord F, Johnson AD, Raffield LM, Curran JE, Blangero J, O'Connell JR, Xu H, Rotter JI, Rich SS, Rice KM, Chen MH, Reiner A, Kooperberg C, Vu T, Hou L, Fornage M, Loos RJF, Kenny E, Mathias R, Becker L, Smith AV, Boerwinkle E, Yu B, Thornton T, Wu MC. General Kernel Machine Methods for Multi-Omics Integration and Genome-Wide Association Testing With Related Individuals. Genet Epidemiol. 2025 Jan; 49(1):e22610.
Score: 0.039
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De La Vega FM, Barnes KC, Fox K, Ioannidis A, Kenny E, Mathias RA, Pasaniuc B. Session Introduction: Overcoming health disparities in precision medicine. Pac Symp Biocomput. 2024; 29:322-326.
Score: 0.037
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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.
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