Abstract: Approaches for generating recommendations for a user related to genetic counseling are provided. A user can be provided with one or more first questions that may be relevant to one or more medical questions. Based at least in part upon one or more answers to the first questions, one or more second questions can be determined and provided to the user. The user can be classified into one or more categories based at least in part upon answers provided to the first questions and the second questions. A recommendation for the user can be generated based at least in part upon the classification of the user.

Abstract: A system configuration and techniques for optimizing schedules and associated use predictions of a multiple resource planning workflow are disclosed herein, applicable to environments such as radiologist scheduling in a teleradiology workflow. In one embodiment, a series of computing engines and components are provided to allow detailed forecasting and the generation of customized recommendations for scheduling and other resource usage scenarios. This forecasting can factor resource efficiencies, changes in resource demand volume, resource specialties, resource usage preferences, expected future events such as the removal or addition of resources at future times, and other resource availability or usage changes. The forecasts may be further enhanced through the use of historical data models and estimated future data models. Additionally, a calendar and other tools may be presented through a user interface to allow forecast and scenario customization based on selection of a series of future dates.

Abstract: A system configuration and techniques for optimizing schedules and associated use predictions of a multiple resource planning workflow are disclosed herein, applicable to environments such as radiologist scheduling in a teleradiology workflow. In one embodiment, a series of computing engines and components are provided to allow detailed forecasting and the generation of customized recommendations for scheduling and other resource usage scenarios. This forecasting can factor resource efficiencies, changes in resource demand volume, resource specialties, resource usage preferences, expected future events such as the removal or addition of resources at future times, and other resource availability or usage changes. The forecasts may be further enhanced through the use of historical data models and estimated future data models. Additionally, a calendar and other tools may be presented through a user interface to allow forecast and scenario customization based on selection of a series of future dates.

Abstract: A system configuration and techniques for optimizing schedules and associated use predictions of a multiple resource planning workflow are disclosed herein, applicable to environments such as radiologist scheduling in a teleradiology workflow. In one embodiment, a series of computing engines and components are provided to allow detailed forecasting and the generation of customized recommendations for scheduling and other resource usage scenarios. This forecasting can factor resource efficiencies, changes in resource demand volume, resource specialties, resource usage preferences, expected future events such as the removal or addition of resources at future times, and other resource availability or usage changes. The forecasts may be further enhanced through the use of historical data models and estimated future data models. Additionally, a calendar and other tools may be presented through a user interface to allow forecast and scenario customization based on selection of a series of future dates.

Abstract: A system configuration and techniques for optimizing schedules and associated use predictions of a multiple resource planning workflow are disclosed herein, applicable to environments such as radiologist scheduling in a teleradiology workflow. In one embodiment, a series of computing engines and components are provided to allow detailed forecasting and the generation of customized recommendations for scheduling and other resource usage scenarios. This forecasting can factor resource efficiencies, changes in resource demand volume, resource specialties, resource usage preferences, expected future events such as the removal or addition of resources at future times, and other resource availability or usage changes. The forecasts may be further enhanced through the use of historical data models and estimated future data models. Additionally, a calendar and other tools may be presented through a user interface to allow forecast and scenario customization based on selection of a series of future dates.