Abstract: The invention relates to a method for detecting a dengue infection in a patient blood sample, comprising the steps: a) Performing an analysis of prespecified parameters of blood platelets and prespecified types of blood cells in the sample and determining parameter values for the prespecified parameters of the platelets and the prespecified types of cells; b) Obtaining sample parameters from the values determined in step a); and c) Evaluating the sample parameters in relation to a prespecified criterion, wherein, if the criterion is fulfilled, a dengue infection is present.

Abstract: There is a need for more effective and efficient constrained-optimization-based operational load balancing. In one example, a method comprises determining constraint-satisfying operator-unit mapping arrangements that satisfy an operator unity constraint and an operator capacity constraint; for each constraint-satisfying operator-unit mapping arrangement, determining an arrangement utility measure; processing each arrangement utility measure using an optimization-based ensemble machine learning model that is configured to determine an optimal operator-unit mapping arrangement of the plurality of constraint-satisfying operator-unit mapping arrangements; and performing one or more operational load balancing operations based on the optimal operator-unit mapping arrangement.

Abstract: There is a need for more effective and efficient predictive data analysis solutions and/or more effective and efficient solutions for generating image representations of categorical data. In one example, embodiments comprise receiving a categorical input feature, generating an image representation of the categorical input feature, generating an image-based prediction based at least in part on the image representation, and performing one or more prediction-based actions based at least in part on the image-based prediction.

Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing risk score generation predictive data analysis. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform risk conformance mining predictive data analysis by utilizing machine learning frameworks that include state processing machine learning models and attribute processing machine learning models, where the machine learning frameworks may be trained as part of generative adversarial machine learning frameworks.

Abstract: There is a need for more effective and efficient predictive data analysis. This need can be addressed by, for example, solutions for performing cross-temporal predictive data analysis. In one example, a method includes determining a time-adjusted encoding for each temporal unit of a group of temporal units, processing each time-adjusted encoding using a cross-temporal encoding machine learning model to generate a cross-temporal encoding of the group of temporal units, and performing one or more prediction-based actions based at least in part on the cross-temporal encoding.

Abstract: There is a need for more effective and efficient constrained-optimization-based operational load balancing. In one example, a method comprises determining constraint-satisfying operator-unit mapping arrangements that satisfy an operator unity constraint and an operator capacity constraint; for each constraint-satisfying operator-unit mapping arrangement, determining an arrangement utility measure; processing each arrangement utility measure using an optimization-based ensemble machine learning model that is configured to determine an optimal operator-unit mapping arrangement of the plurality of constraint-satisfying operator-unit mapping arrangements; and performing one or more operational load balancing operations based on the optimal operator-unit mapping arrangement.

Abstract: There is a need for solutions for more efficient predictive data analysis systems. This need can be addressed, for example, by a system configured to receive temporal inferences for a predictive task, where each temporal inference is associated with a temporal benchmark and the temporal benchmarks include a base temporal benchmark and supplemental temporal benchmarks; generate a cross-temporal prediction for the predictive task by applying one or more cross-temporal probabilistic updates to the base temporal inference, where each cross-temporal probabilistic update is associated with a supplemental temporal benchmark; and display the cross-temporal prediction using a cross-temporal prediction interface.

Abstract: There is a need for solutions for more efficient predictive data analysis systems. This need can be addressed, for example, by a system configured to obtain, for each predictive task of a plurality of predictive tasks, a plurality of per-model inferences; generate, for each predictive task, a cross-model prediction based on the plurality of per-model inferences for the predictive task; and generate, based on each cross-model prediction associated with a predictive task, a cross-prediction for the particular predictive task, wherein determining the cross-prediction comprises applying one or more probabilistic updates to the cross-model prediction for the particular predictive task and each probabilistic update is determined based on the cross-model prediction for a related predictive task of the one or more related predictive tasks.

Abstract: The invention relates to a method for detecting a dengue infection in a patient blood sample, comprising the steps: a) Performing an analysis of prespecified parameters of blood platelets and prespecified types of blood cells in the sample and determining parameter values for the prespecified parameters of the platelets and the prespecified types of cells; b) Obtaining sample parameters from the values determined in step a); and c) Evaluating the sample parameters in relation to a prespecified criterion, wherein, if the criterion is fulfilled, a dengue infection is present.

Abstract: The present invention provides topical formulations containing a vitamin K analog, e.g., menadione, that deliver a uniform, therapeutically effective concentration of the vitamin K analog to the skin in a vehicle which is stable, non-irritating, non-drying and cosmetically acceptable. These topical formulations are useful for the treatment and prevention of dermatological conditions associated with inflammation, particularly, dermatological conditions resulting from anti-EGFR therapies.

Abstract: The present invention provides topical formulations containing a vitamin K analog, e.g., menadione, that deliver a uniform, therapeutically effective concentration of the vitamin K analog to the skin in a vehicle which is stable, non-irritating, non-drying and cosmetically acceptable. These topical formulations are useful for the treatment and prevention of dermatological conditions associated with inflammation, particularly, dermatological conditions resulting from anti-EGFR therapies.

Abstract: The present invention provides topical formulations containing a vitamin K analog, e.g., menadione, that deliver a uniform, therapeutically effective concentration of the vitamin K analog to the skin in a vehicle which is stable, non-irritating, non-drying and cosmetically acceptable. These topical formulations are useful for the treatment and prevention of dermatological conditions associated with inflammation, particularly, dermatological conditions resulting from anti-EGFR therapies.