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Artificial intelligence enables comprehensive genome interpretation and nomination of candidate diagnoses for rare genetic diseases
BACKGROUND: Clinical interpretation of genetic variants in the context of the patient’s phenotype is becoming the largest component of cost and time expenditure for genome-based diagnosis of rare genetic diseases. Artificial intelligence (AI) holds promise to greatly simplify and speed genome interp...
Autores principales: | De La Vega, Francisco M., Chowdhury, Shimul, Moore, Barry, Frise, Erwin, McCarthy, Jeanette, Hernandez, Edgar Javier, Wong, Terence, James, Kiely, Guidugli, Lucia, Agrawal, Pankaj B., Genetti, Casie A., Brownstein, Catherine A., Beggs, Alan H., Löscher, Britt-Sabina, Franke, Andre, Boone, Braden, Levy, Shawn E., Õunap, Katrin, Pajusalu, Sander, Huentelman, Matt, Ramsey, Keri, Naymik, Marcus, Narayanan, Vinodh, Veeraraghavan, Narayanan, Billings, Paul, Reese, Martin G., Yandell, Mark, Kingsmore, Stephen F. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8515723/ https://www.ncbi.nlm.nih.gov/pubmed/34645491 http://dx.doi.org/10.1186/s13073-021-00965-0 |
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