Abstract: Embodiments of the invention may help improve the accuracy of individually tailored prognoses in dealing with individual patient prognoses for cancer, diabetes, multiple sclerosis, heart disease, and/or other diseases. Alternate embodiments of the invention may be useful in improving the accuracy of predictions in a variety of other contexts and fields. A method according to various embodiments of the invention includes generating a univariate impact reflecting index (UIRI) based on an indicator, the indicator having a monotonic relationship to a focal conclusion, wherein the UIRI spaces subscales of the indicator according to a magnitude of impact of the indicator to the focal conclusion.

Abstract: Embodiments of the invention may help improve the accuracy of individually tailored prognoses in dealing with individual patient prognoses for cancer, diabetes, multiple sclerosis, heart disease, and/or other diseases. Alternate embodiments of the invention may be useful in improving the accuracy of predictions in a variety of other contexts and fields. A method according to various embodiments of the invention includes generating a univariate impact reflecting index (UIRI) based on an indicator, the indicator having a monotonic relationship to a focal conclusion, wherein the UIRI spaces subscales of the indicator according to a magnitude of impact of the indicator to the focal conclusion.

Abstract: Embodiments of the invention may help improve the accuracy of individually tailored prognoses in dealing with individual patient prognoses for cancer, diabetes, multiple sclerosis, heart disease, and/or other diseases. Alternate embodiments of the invention may be useful in improving the accuracy of predictions in a variety of other contexts and fields. A method according to various embodiments of the invention includes generating a univariate impact reflecting index (UIRI) based on an indicator, the indicator having a monotonic relationship to a focal conclusion; and determining a probability that the focal conclusion will occur, wherein determining the probability is based at least partially on a regression analysis of the UIRI.

Abstract: Embodiments of the invention may help improve the accuracy of individually tailored prognoses in dealing with individual patient prognoses for cancer, diabetes, multiple sclerosis, heart disease, and/or other diseases. Alternate embodiments of the invention may be useful in improving the accuracy of predictions in a variety of other contexts and fields. A method according to various embodiments of the invention includes generating a univariate impact reflecting index (UIRI) based on an indicator, the indicator having a monotonic relationship to a focal conclusion; and determining a probability that the focal conclusion will occur, wherein determining the probability is based at least partially on a regression analysis of the UIRI.

Abstract: A system for determining selections that a user is likely to be interested in. The determination is made based on the user's prior indicated preferences. The user designates his or her preferred selections as entries in a user's preference list. Entries in the user's list are compared with entries in the other users' lists. When a significant number of matches have been found between two lists, the unmatched entries of the other user's preference list are extracted. The unmatched entries are further processed. Those unmatched entries with a high correlation to the user's preference list are presented to the user as selections in which the user is likely to be interested.

Abstract: A system for determining selections that a user is likely to be interested in. The determination is made based on the user's prior indicated preferences. The user designates his or her preferred selections as entries in a user's preference list. Entries in the user's list are compared with entries in the other users' lists. When a significant number of matches have been found between two lists, the unmatched entries of the other user's preference list are extracted. The unmatched entries are further processed. Those unmatched entries with a high correlation to the user's preference list are presented to the user as selections in which the user is likely to be interested.

Abstract: A system for determining selections that a user is likely to be interested in. The determination is made based on the user's prior indicated preferences. The user designates his or her preferred selections as entries in a user's preference list. Entries in the user's list are compared with entries in the other users' lists. When a significant number of matches have been found between two lists, the unmatched entries of the other user's preference list are extracted. The unmatched entries are further processed. Those unmatched entries with a high correlation to the user's preference list are presented to the user as selections in which the user is likely to be interested.