Thea Norman

发表

The inconvenience of data of convenience: computational research beyond post-mortem analyses

Krister Wennerberg, Tero Aittokallio, Emmanuel Barillot, 2017, Nature Methods.

A Crowdsourcing Approach to Developing and Assessing Prediction Algorithms for AML Prognosis

Li Liu, Raquel Norel, Paul C. Boutros, 2016, PLoS Comput. Biol..

Report on the Cloud-Based Evaluation Approaches Workshop 2015

Allan Hanbury, Antonio Criminisi, Henning Müller, 2016, SIGIR Forum.

Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms

Berkman Sahiner, Jaime S. Cardoso, Thomas Yu, 2020, JAMA network open.

A Structure-Based Library Approach to Kinase Inhibitors

Peter G. Schultz, Thea Norman, Nathanael S. Gray, 1996 .

The Prostate Cancer DREAM Challenge: A Community-Wide Effort to Use Open Clinical Trial Data for the Quantitative Prediction of Outcomes in Metastatic Prostate Cancer.

Gustavo Stolovitzky, Thea Norman, Stephen Friend, 2015, The oncologist.

Reducing overfitting in challenge-based competitions

Thomas Yu, Pablo Meyer, Justin Guinney, 2016, 1607.00091.

Combining accurate tumor genome simulation with crowdsourcing to benchmark somatic structural variant detection

David Haussler, Justin Guinney, Zechen Chong, 2018, bioRxiv.

Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

Matti Pirinen, Jukka Corander, Krister Wennerberg, 2016, Nature Communications.

Stratification of amyotrophic lateral sclerosis patients: a crowdsourcing approach

Jung-Hsien Chiang, Devin C. Koestler, Celine Vens, 2018, Scientific Reports.

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open clinical trial data.

Thomas Yu, Tapio Pahikkala, Antti Airola, 2017, The Lancet. Oncology.