Genetic risk profiles for cancer susceptibility and therapy response.

By H. Bartsch, H. Dally, O. Popanda, A. Risch, P. Schmezer. 2007

77 citations recorded by the source corpus.

Subfields: Molecular Biology, Pulmonary and Respiratory Medicine

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. Bryan Lim
2. Ahmed M. Alaa
3. Mihaela van der Schaar
4. James Jordon
5. Ioana Bica

In Pulmonary and Respiratory Medicine

1. Ahmed M. Alaa
2. Mihaela van der Schaar
3. Ioana Bica

Citations in the corpus

• Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders (2019, methodology): “To account for heterogeneity among patient responses, due to, for example genetic features (Bartsch et al., 2007), the prior means for βc and αr are adjusted according to the three patient subgroups as described in (Lim et al., 2018).”
• Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations (2020, methodology): “To incorporate heterogeneity among patient responses, due to, for instance, gender or genetic factors Bartsch et al. (2007), the prior means for β c and α r are adjusted to create three patient subgroups S ( i ) ∈ { 1 , 2 , 3 as described in Lim et al. (2018).”
• Forecasting Treatment Responses Over Time Using Recurrent Marginal Structural Networks (2018, background): “by genetic factors [4]), which augment the prior means of βc and α according to:”