Abstract: A method and a system for managing a process of pathology examination may include an image-analysis module, configured to receive at least one digital scan of at least one pathology slide related to a pathology case, and perform at least one algorithm of image analysis thereon to extract at least one clinical feature of the at least one slide; a human-machine interface, adapted to present the at least one digital scan on a screen; a machine-learning based module, adapted to classify the at least one pathology slide to a classification of a set of classifications based on at least one clinical feature, the set of classifications selected from a list consisting a low risk classification and a high risk classification; and a report module, adapted to produce, in real time, at least one report data element comprising diagnostic information, based on the classification of the at least one pathology slide.

Abstract: A method and system for personalization of digital pathology analysis, may include: an image-analysis based diagnostics module, configured to extract at least one feature of a digital scan of a pathology slide of a patient, a human-machine interface module, configured to present the digital scan to a user for examination and at least one machine learning module, configured to produce at least one personalized suggestion according to the at least one extracted slide feature.

Abstract: Methods and systems are described for providing cost effective leak detection in a fluid network. Step testing procedures are represented by decision trees and associated expected costs are calculated. Selection of step testing procedures is optimized for low expected cost. The total expected cost rate for a network configuration may be calculated from the rate of leak occurrence and the optimal expected costs associated therewith. Network configuration changes may be recommended by optimizing for total expected cost rate for a fluid network.

Abstract: A computerized method for modeling a utility network. The method includes retrieving geographical information system (GIS) data, asset management data, and sensor archive data of one or more assets of the utility network. The method also includes generating one or more mathematical elements from the one or more assets and creating probable connections between the one or more mathematical graph elements based on the GIS and asset data. A mathematical graph is generated based on the probable connections, the mathematical graph including one or more asset characteristics of the one or more assets. Analysis is performed on the utility network using the mathematical graph and the mathematical graph data is stored for use by other systems within the utility network.

Abstract: Methods and systems are described for providing cost effective leak detection in a fluid network. Step testing procedures are represented by decision trees and associated expected costs are calculated. Selection of step testing procedures is optimized for low expected cost. The total expected cost rate for a network configuration may be calculated from the rate of leak occurrence and the optimal expected costs associated therewith. Network configuration changes may be recommended by optimizing for total expected cost rate for a fluid network.

Abstract: A computerized method for modeling a utility network. The method includes retrieving geographical information system (GIS) data, asset management data, and sensor archive data of one or more assets of the utility network. The method also includes generating one or more mathematical elements from the one or more assets and creating probable connections between the one or more mathematical graph elements based on the GIS and asset data. A mathematical graph is generated based on the probable connections, the mathematical graph including one or more asset characteristics of the one or more assets. Analysis is performed on the utility network using the mathematical graph and the mathematical graph data is stored for use by other systems within the utility network.

Abstract: A computerized method for detecting related events in a water monitoring system. The method includes receiving event data from a plurality of sensors in a water network. The method also includes identifying at least two candidate events from the event data as being candidate events which are likely to constitute part of a common anomaly event, the candidate events each being substantially anomalous. An event combination rule is selected. One or more event characteristics are compared between the at least two candidate events based on the event combination rule. The at least two candidate events are determined whether they are related and associated with a common event causing the at least two candidate events on the basis of the comparison. The determination of the at least two candidate events are related and associated with a common event is reported to a user via a user interface.