Abstract: In one embodiment, a viewing behavior subsystem computes estimated viewership among target audiences at a person-level based on a household viewing logs and person-level data. A viewing behavior subsystem distributes the household viewing logs across buckets based on the sizes of the households and sets of person-level characteristics that are associated with the persons within the households. The viewing behavior subsystem generates a model for viewing behaviors associated with different sets of person-level characteristics based on the buckets. Subsequently, the viewing behavior subsystem estimates viewership among a target audience that is associated with one or more of the sets of person-level characteristics based on the model and census data.

Abstract: Disclosed is a gene expression panel that can predict radiation sensitivity (radiosensitivity) of a tumor in a subject. A method of predicting radiation sensitivity is provided that is based on cellular clonogenic survival after 2 Gy (SF2) for 48 cell lines. Gene expression is used as the basis of the prediction model. The radiosensitivity cell-based prediction model is validated using clinical patient data from rectal and esophagus cancer patients that received RT before surgery. The radiosensitivity genomic-based prediction model identifies patients with rectal cancer that may benefit from RT treatment by assigning higher values of SF2 to radio-resistant patients and lower values of SF2 to radio-sensitive patients.

Abstract: In one embodiment, a promotional subsystem generates promotional plans that include promotionals, where each promotional targets one or more pieces of scheduled content. First, the promotional subsystem generates a statistical model based on historical respondent viewership data. The statistical model model maps a respondent viewing of a promotional that targets a piece of scheduled content to a probability of the respondent viewing the piece of scheduled content. Subsequently, the promotional subsystem generates a proposed promotional plan based on the statistical model, a schedule that includes the piece of scheduled content, and a risk tolerance. Advantageously, the promotional subsystem may be configured to generate different proposed promotional plans based on different risk tolerances associated with different viewership growth strategies.

Abstract: Disclosed is a gene expression panel that can predict radiation sensitivity (radiosensitivity) of a tumor in a subject. A method of predicting radiation sensitivity is provided that is based on cellular clonogenic survival after 2 Gy (SF2) for 48 cell lines. Gene expression is used as the basis of the prediction model. The radiosensitivity cell-based prediction model is validated using clinical patient data from rectal and esophagus cancer patients that received RT before surgery. The radiosensitivity genomic-based prediction model identifies patients with rectal cancer that may benefit from RT treatment by assigning higher values of SF2 to radio-resistant patients and lower values of SF2 to radio-sensitive patients.

Abstract: In one embodiment, a promotional subsystem generates promotional plans that include promotionals, where each promotional targets one or more pieces of scheduled content. First, the promotional subsystem generates a statistical model based on historical respondent viewership data. The statistical model model maps a respondent viewing of a promotional that targets a piece of scheduled content to a probability of the respondent viewing the piece of scheduled content. Subsequently, the promotional subsystem generates a proposed promotional plan based on the statistical model, a schedule that includes the piece of scheduled content, and a risk tolerance. Advantageously, the promotional subsystem may be configured to generate different proposed promotional plans based on different risk tolerances associated with different viewership growth strategies.

Abstract: In one embodiment, a viewing behavior subsystem computes estimated viewership among target audiences at a person-level based on a household viewing logs and person-level data. A viewing behavior subsystem distributes the household viewing logs across buckets based on the sizes of the households and sets of person-level characteristics that are associated with the persons within the households. The viewing behavior subsystem generates a model for viewing behaviors associated with different sets of person-level characteristics based on the buckets. Subsequently, the viewing behavior subsystem estimates viewership among a target audience that is associated with one or more of the sets of person-level characteristics based on the model and census data.

Abstract: Disclosed is a gene expression panel that can predict radiation sensitivity (radiosensitivity) of a tumor in a subject. A method of predicting radiation sensitivity is provided that is based on cellular clonogenic survival after 2 Gy (SF2) for 48 cell lines. Gene expression is used as the basis of the prediction model. The radiosensitivity cell-based prediction model is validated using clinical patient data from rectal and esophagus cancer patients that received RT before surgery. The radiosensitivity genomic-based pre-diction model identifies patients with rectal cancer that may benefit from RT treatment by assigning higher values of SF2 to radio-resistant patients and lower values of SF2 to radio-sensitive patients.