Sieh, Weiva

REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants

Ioannidis, N. M., Rothstein, J. H., Pejaver, V., Middha, S., McDonnell, S. K., Baheti, S., Musolf, A., Li, Q., Holzinger, E., Karyadi, D., et al. (2016) · The American Journal of Human Genetics

Genomics and Rare DiseasesGenetic Associations and Epidemiology

Cited by 2,908

Proteogenomic and metabolomic characterization of human glioblastoma

Wang, L.-B., Karpova, A., Gritsenko, M. A., Kyle, J. E., Cao, S., Li, Y., Rykunov, D., Colaprico, A., Rothstein, J. H., Hong, R., et al. (2021) · Cancer Cell

Glioma Diagnosis and TreatmentCancer Genomics and Diagnostics

Cited by 661

Evaluation of combined artificial intelligence and radiologist assessment to interpret screening mammograms

Schaffter, T., Buist, D. S. M., Lee, C. I., Nikulin, Y., Ribli, D., Guan, Y., Lotter, W., Jie, Z., Du, H., Wang, S., et al. (2020) · JAMA Network Open

AI in cancer detectionDigital Radiography and Breast Imaging

Cited by 409

Identification of six new susceptibility loci for invasive epithelial ovarian cancer

EMBRACE, Kuchenbaecker, K. B., Collaborators, G. S., Breast Cancer Family Registry, HEBON, KConFab Investigators, Australian Cancer Study (Ovarian Cancer Investigators), Australian Ovarian Cancer Study Group, the Consortium of Investigators of Modifiers of BRCA1 and BRCA2, Ramus, S. J., et al. (2015) · Nature Genetics

BRCA gene mutations in cancerOvarian cancer diagnosis and treatment

Cited by 250

Comparison of mammography AI algorithms with a clinical risk model for 5-year breast cancer risk prediction: an observational study

Arasu, V. A., Habel, L. A., Achacoso, N. S., Buist, D. S. M., Cord, J. B., Esserman, L. J., Hylton, N. M., Glymour, M. M., Kornak, J., Kushi, L. H., et al. (2023) · Radiology

Digital Radiography and Breast ImagingAI in cancer detection

Cited by 98