Gao, Jianjiong

Multimodal data integration using machine learning improves risk stratification of high-grade serous ovarian cancer

Boehm, K. M., Aherne, E. A., Ellenson, L., Nikolovski, I., Alghamdi, M., Vázquez-García, I., Zamarin, D., Long Roche, K., Liu, Y., Patel, D., et al. (2022) · Nature Cancer

Ovarian cancer diagnosis and treatmentRadiomics and Machine Learning in Medical Imaging

Cited by 357

Disruption of chromatin folding domains by somatic genomic rearrangements in human cancer

Akdemir, K. C., Le, V. T., Chandran, S., Li, Y., Verhaak, R. G., Beroukhim, R., Campbell, P. J., Chin, L., Dixon, J. R., Futreal, P. A., et al. (2020) · Nature Genetics

Genomics and Chromatin DynamicsChromatin Remodeling and Cancer

Cited by 283

Automated Real-World Data Integration Improves Cancer Outcome Prediction

Jee, J., Fong, C., Pichotta, K., Tran, T. N., Luthra, A., Waters, M., Fu, C., Altoe, M., Liu, S.-Y., Maron, S. B., et al. (2024) · Nature

Machine Learning in HealthcareCancer Genomics and Diagnostics

Cited by 188

Comprehensive pan-genomic characterization of adrenocortical carcinoma

Zheng, S., Cherniack, A. D., Dewal, N., Moffitt, R. A., Danilova, L., Murray, B. A., Lerario, A. M., Else, T., Knijnenburg, T. A., Ciriello, G., et al. (2016) · Cancer Cell

Adrenal and Paraganglionic TumorsChromatin Remodeling and Cancer

Cited by 165

A harmonized meta-knowledgebase of clinical interpretations of somatic genomic variants in cancer

Variant Interpretation for Cancer Consortium, Wagner, A. H., Walsh, B., Mayfield, G., Tamborero, D., Sonkin, D., Krysiak, K., Deu-Pons, J., Duren, R. P., Gao, J., et al. (2020) · Nature Genetics

Genomics and Rare DiseasesCancer Genomics and Diagnostics

Cited by 164

Abstract 99: Evolution of OncoKB, a precision oncology knowledgebase

Suehnholz, S. P., Kundra, R., Zhang, H., Smith, S., Nissan, M., Yao, Y., LaFave, L., Gala, K., Miles, L., Arcila, M. E., et al. (2021) · Cancer Research

Cancer Genomics and DiagnosticsGenomics and Rare Diseases

Cited by 3