Abstract: A method for determining a disease state prediction, relating to a potential disease or medical condition of a subject, includes accessing a set of subject images, the subject images capturing a part of a subject's body, and accessing a set of clinical factors from the subject. The clinical factors are collected by a device or a medical practitioner substantially contemporaneously with the capture of the subject images. The subject images are inputted into an image model to generate disease metrics for disease prediction for the subject. The disease metrics generated by the image model and the clinical factors are inputted into a classifier to determine the disease state prediction, and the disease state prediction is returned.

Abstract: A method for determining a disease state prediction, relating to a potential disease or medical condition of a subject, includes accessing a set of subject images, the subject images capturing a part of a subject's body, and accessing a set of clinical factors from the subject. The clinical factors are collected by a device or a medical practitioner substantially contemporaneously with the capture of the subject images. The subject images are inputted into an image model to generate disease metrics for disease prediction for the subject. The disease metrics generated by the image model and the clinical factors are inputted into a classifier to determine the disease state prediction, and the disease state prediction is returned.

Abstract: A method for determining a disease state prediction, relating to a potential disease or medical condition of a subject, includes accessing a set of subject images, the subject images capturing a part of a subject's body, and accessing a set of clinical factors from the subject. The clinical factors are collected by a device or a medical practitioner substantially contemporaneously with the capture of the subject images. The subject images are inputted into an image model to generate disease metrics for disease prediction for the subject. The disease metrics generated by the image model and the clinical factors are inputted into a classifier to determine the disease state prediction, and the disease state prediction is returned.

Abstract: Systems and methods are provided for feedback-driven provision of information in relation to a plurality of information resources.

Abstract: Systems and methods are provided for feedback-driven provision of information in relation to a plurality of information resources.

Abstract: Systems and methods are disclosed for management of a fleet of machines operating in a construction and/or civil engineering project. Telematics data is received from first and second machines at regular intervals. Positional and temporal proximity is determined between the first and second machines based at least in part on an analysis of the telematics data, indicating for example that the first machine is within a predetermined maximum distance of the second machine for at least a predetermined minimum duration. If there is positional and temporal proximity, work cycle data is received from the machines and is correlated. If there is a correlation in the work cycle data, an association is generated between the first and second machines and the association is applied to enable inheritance of material type between the first and second machines to support automated mass haul monitoring, and generate and implement a construction plan.

Abstract: A method for determining a disease state prediction, relating to a potential disease or medical condition of a subject, includes accessing a set of subject images, the subject images capturing a part of a subject's body, and accessing a set of clinical factors from the subject. The clinical factors are collected by a device or a medical practitioner substantially contemporaneously with the capture of the subject images. The subject images are inputted into an image data model to generate disease metrics for disease prediction for the subject. The disease metrics generated by the image data model and the clinical factors are inputted into a classifier to determine the disease state prediction, and the disease state prediction is returned.

Abstract: A method for determining a disease state prediction, relating to a potential disease or medical condition of a subject, includes accessing a set of subject images, the subject images capturing a part of a subject's body, and accessing a set of clinical factors from the subject. The clinical factors are collected by a device or a medical practitioner substantially contemporaneously with the capture of the subject images. The subject images are inputted into an image model to generate disease metrics for disease prediction for the subject. The disease metrics generated by the image model and the clinical factors are inputted into a classifier to determine the disease state prediction, and the disease state prediction is returned.

Abstract: Systems and methods are provided for feedback-driven provision of information in relation to a plurality of information resources.

Abstract: Systems and methods are provided for feedback-driven provision of information in relation to a plurality of information resources.

Abstract: Systems and methods are provided for feedback-driven provision of information in relation to a plurality of information resources.

Abstract: Systems and methods are provided for feedback-driven provision of information in relation to a plurality of information resources.

Abstract: Systems and methods are provided for feedback-driven provision of information in relation to a plurality of information resources.

Abstract: Systems and methods are provided for feedback-driven provision of information in relation to a plurality of information resources. Some such methods involve: accessing information resources from repositories to establish a mapping between information resources; maintaining a state table comprising a plurality of state-table records, each state-table record attributing a value to a state-action pair, which comprises an indication of actions in relation to the information resources; monitoring actions of a user in relation to the information resources; receiving a feedback metric related to interaction of the user with the information resources; using the feedback metric to update the values of the state-table records; and providing output information based at least in part on the updated values of the state-table records.

Abstract: Systems and methods are provided for feedback-driven provision of information in relation to a plurality of information resources. Some such methods involve: accessing information resources from repositories to establish a mapping between information resources; maintaining a state table comprising a plurality of state-table records, each state-table record attributing a value to a state-action pair, which comprises an indication of actions in relation to the information resources; monitoring actions of a user in relation to the information resources; receiving a feedback metric related to interaction of the user with the information resources; using the feedback metric to update the values of the state-table records; and providing output information based at least in part on the updated values of the state-table records.