Abstract: Techniques are generally described for onboarding optimization for new hires. In various examples, labor order data specifying a target number of new hires may be received. In some examples, a first machine learning model may predict a number of new hire appointments to offer based at least in part on the labor order data. In further examples, an optimization component may allocate the number of new hire appointments to respective time slots based at least in part on candidate preferences. In some additional examples, data may be sent to a first application effective to display a list of available new hire appointment time slots of the respective time slots.

Abstract: A variety of systems, methods, and articles of manufacture are disclosed. An example includes accessing of patient deviation scores indicative of differences between patient data and reference data representative of a population segment, wherein the patient deviation scores are derived from longitudinal data of the patient data such that the patient deviation scores include a plurality of sets of patient deviation scores, each set indicative of differences between patient data collected at a respective point in time and the reference data; identifying a trend in the patient deviation scores for at least one clinical parameter; generating of a report including a visual indication of the trend; and outputting of the report. The report includes one or more views including Z, T, D, DT, and D feedback on T views, using image and non-image data.

Abstract: A system comprising a memory device having a plurality of routines stored therein, a processor configured to execute the plurality of routines stored in the memory device, the plurality of routines comprising: a routine configured to effect, when executed, accessing of patient deviation scores indicative of differences between patient data and reference data representative of a population segment, wherein the patient deviation scores are derived from longitudinal data of the patient data such that the patient deviation scores include a plurality of sets of patient deviation scores, each set indicative of differences between patient data collected at a respective point in time and the reference data; a routine configured to effect, when executed, identifying a trend in the patient deviation scores for at least one clinical parameter; a routine configured to effect, when executed, generating of a report including a visual indication of the trend; and a routine configured to effect, when executed, outputting of

Abstract: Methods and apparatus for determining brain cortical thickness are provided. One method includes determining an intensity profile at each of a plurality of cortical surface points of an imaged brain using brain tissue image data and calculating a cortical thickness based on a parametrically determined transition point of each intensity profile.

Abstract: Certain examples provide systems and methods for holistic viewing to provide comparative analysis and decision support in a drug development process. An example method includes a computer-implemented method for assessing drug efficacy, comprising: accessing a first data set related to the performance of a target drug for a given indication; accessing a second data set related to a control for the indication; comparing the data for the target drug and the data for the control on at least one of a plurality of different metrics using a holistic analysis, wherein the at least one metric corresponds to an outcome associated with the indication and generating a corresponding report.

Abstract: A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing reference deviation maps for a plurality of disease types. The reference deviation maps may include subsets of maps associated with severity levels of respective disease types, and a disease severity score may be associated with each severity level. The method may include selecting patient severity levels for multiple disease types based on the subsets of reference deviation maps. Also, the method may include automatically calculating a combined patient disease severity score based at least in part on the disease severity scores associated with the selected patient severity levels, and may include outputting a report based at least in part on the combined patient disease severity score. Additional methods, systems, and manufactures are also disclosed.

Abstract: A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing patient image and non-image deviation scores derived through respective comparisons of patient image and non-image data to standardized image and non-image data. The method may also include processing the image and non-image deviation scores to generate a visual output indicative of differences between the patient image and non-image data, and the standardized image and non-image data, respectively. Further, the method may include displaying the visual output. Additional methods, systems, and manufactures are also disclosed.

Abstract: Certain examples provide systems and methods for holistic viewing to provide comparative analysis and decision support in a drug development process. An example method includes a computer-implemented method for assessing drug efficacy, comprising: accessing a first data set related to the performance of a target drug for a given indication; accessing a second data set related to a control for the indication; comparing the data for the target drug and the data for the control on at least one of a plurality of different metrics using a holistic analysis, wherein the at least one metric corresponds to an outcome associated with the indication and generating a corresponding report.

Abstract: Certain examples provide systems and methods for holistic viewing to provide comparative analysis and decision support in a drug development process, and safety testing. An example method includes providing a first set of data corresponding to a drug of interest; providing a reference set of drug interaction data, comparing the first set of data to the reference set using a holistic analysis, and reporting the results of the comparison. An example of the holistic analysis and viewing apparatus for drug safety comprises a standardizer to at least one of standardize and normalize drug interaction data related to drug safety; a deviation analyzer to compare the drug interaction data to data corresponding to a drug under review using a holistic analysis, and a reporter for reporting the output of the deviation analyzer.

Abstract: A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing individual patient deviation maps indicative of a structural difference and a functional difference, respectively, of at least one anatomical region of a patient with respect to standardized reference image data. The method may also include generating a composite patient deviation map indicative of both the structural difference and the functional difference based on at least the individual patient deviation maps, and outputting the composite patient deviation map. Additional methods, systems, and manufactures are also disclosed.

Abstract: A system comprising a memory device having a plurality of routines stored therein, a processor configured to execute the plurality of routines stored in the memory device, the plurality of routines comprising: a routine configured to effect, when executed, accessing of patient deviation scores indicative of differences between patient data and reference data representative of a population segment, wherein the patient deviation scores are derived from longitudinal data of the patient data such that the patient deviation scores include a plurality of sets of patient deviation scores, each set indicative of differences between patient data collected at a respective point in time and the reference data; a routine configured to effect, when executed, identifying a trend in the patient deviation scores for at least one clinical parameter; a routine configured to effect, when executed, generating of a report including a visual indication of the trend; and a routine configured to effect, when executed, outputting of

Abstract: Systems, methods and computer-readable storage mediums encoded with instructions for providing touch-driven controls in a clinical setting are provided. Certain embodiments provide a system that includes a clinical system and a customizable structured library of functions. The structured library can include a function associated with a clinical context. The function can be associated with a user input requiring the use of a touch driven interface with multi-touch gestures. The user input can provide for immediate execution of the associated function. The structured library can be loaded onto the clinical system as a driver such that the function is made available based on the associated clinical context. Certain embodiments can include a user interface configured to allow a user to add or delete a function or modify the user input associated with a function. Certain embodiments can include a user interface that provides instruction as to using a function.

Abstract: A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing patient deviation data of a structural difference between a patient anatomical feature and a standardized anatomical feature. The method may also include comparing the patient deviation data to reference deviation data sets representative of multiple disease types. Each reference deviation data set may be representative of an expected deviation from the standardized anatomical feature for a particular disease type. The method may further include automatically identifying one or more potential patient disease types based at least in part on the comparison. Additional methods, systems, and manufactures are also disclosed.

Abstract: A system and method for detecting, diagnosing, and monitoring a disease and determining a disease signature including accessing patient deviation scores indicative of differences between patient data and reference data representative of a population segment, the patient deviation scores derived from longitudinal patient data such that the patient deviation scores include a plurality of sets of patient deviation scores, each set indicative of differences between patient data collected at a respective point in time and the reference data. The system and method also includes identifying a trend in the patient deviation scores for at least one clinical parameter, generating a report including a visual indication of the trend, and outputting the report. The report includes one or more views including Z, T, D, DT, and D feedback on T views, using image and non-image data.

Abstract: A system and method for detecting, diagnosing, and monitoring a disease and determining a disease signature including accessing patient deviation scores indicative of differences between patient data and reference data representative of a population segment, the patient deviation scores derived from longitudinal patient data such that the patient deviation scores include a plurality of sets of patient deviation scores, each set indicative of differences between patient data collected at a respective point in time and the reference data. The system and method also includes identifying a trend in the patient deviation scores for at least one clinical parameter, generating a report including a visual indication of the trend, and outputting the report. The report includes one or more views including Z, T, D, DT, and D feedback on T views, using image and non-image data.

Abstract: A system and method for detecting, diagnosing, and monitoring a disease and determining a disease signature including accessing patient deviation scores indicative of differences between patient data and reference data representative of a population segment, the patient deviation scores derived from longitudinal patient data such that the patient deviation scores include a plurality of sets of patient deviation scores, each set indicative of differences between patient data collected at a respective point in time and the reference data. The system and method also includes identifying a trend in the patient deviation scores for at least one clinical parameter, generating a report including a visual indication of the trend, and outputting the report. The report includes one or more views including Z, T, D, DT, and D feedback on T views, using image and non-image data.

Abstract: Methods and apparatus for determining brain cortical thickness. One method includes determining an intensity profile at each of a plurality of cortical surface points of an imaged brain using brain tissue image data and calculating a cortical thickness based on a parametrically determined transition point of each intensity profile.

Abstract: A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing patient deviation data of a structural difference between a patient anatomical feature and a standardized anatomical feature. The method may also include comparing the patient deviation data to reference deviation data sets representative of multiple disease types. Each reference deviation data set may be representative of an expected deviation from the standardized anatomical feature for a particular disease type. The method may further include automatically identifying one or more potential patient disease types based at least in part on the comparison. Additional methods, systems, and manufactures are also disclosed.

Abstract: A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing individual patient deviation maps indicative of a structural difference and a functional difference, respectively, of at least one anatomical region of a patient with respect to standardized reference image data. The method may also include generating a composite patient deviation map indicative of both the structural difference and the functional difference based on at least the individual patient deviation maps, and outputting the composite patient deviation map. Additional methods, systems, and manufactures are also disclosed.

Abstract: A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing reference deviation maps for a plurality of disease types. The reference deviation maps may include subsets of maps associated with severity levels of respective disease types, and a disease severity score may be associated with each severity level. The method may include selecting patient severity levels for multiple disease types based on the subsets of reference deviation maps. Also, the method may include automatically calculating a combined patient disease severity score based at least in part on the disease severity scores associated with the selected patient severity levels, and may include outputting a report based at least in part on the combined patient disease severity score. Additional methods, systems, and manufactures are also disclosed.