Abstract: A computer implemented method of creating a clustering model used for clustering a plurality of log messages comprising using one or more processors for receiving a plurality of training log messages, performing the following for each of the plurality of training log messages: calculating a string distance between a textual content of the respective training log message and a representative string pattern of each of the plurality of clusters, associating the respective training log message with a respective one of the plurality of clusters in case the string distance is within a predefined threshold and adding a new cluster to the plurality of clusters for associating respective training log message in case the string distance exceeds the predefined threshold, and outputting the clustering model.

Abstract: A system for generating approximately coordinated region maps (RM), the system comprising a processing resource configured to: provide a data repository comprising one or more RMs, each mapping a corresponding region, and each including information of a relative location of synchronization objects (SOs) located within the corresponding region with respect to a coordinate-system (CS) origin of a CS of the corresponding RM; obtain a given RM including information of relative locations of given SOs located within the given region with respect to a given CS origin of a given CS of the given RM; retrieve, from the data repository, reference RMs that meet a criteria; identify the reference RMs associated with at least one SO that match at least one of the given SO, giving rise to optimization RMs; and determine, utilizing an optimization scheme, an approximate transformation between the given CS and the CSs of the optimization RMs.

Abstract: Method of predicting a response of a subject to food is disclosed. The method comprises: selecting a food to which a response of the subject is unknown; accessing a first database having data describing the subject but not a response of the subject to the selected food; accessing a second database having data pertaining to responses of other subjects to foods, the responses of the other subjects including responses of at least one other subject to the selected food or a food similar to said selected food; and analyzing the databases based on the selected food to estimate the response of the subject to the selected food.

Abstract: Method of predicting a response of a subject to food is disclosed. The method comprises: selecting a food to which a response of the subject is unknown; accessing a first database having data describing the subject but not a response of the subject to the selected food; accessing a second database having data pertaining to responses of other subjects to foods, the responses of the other subjects including responses of at least one other subject to the selected food or a food similar to said selected food; and analyzing the databases based on the selected food to estimate the response of the subject to the selected food.

Abstract: A method of predicting an analyte level comprises receiving a time-ordered series of levels of the analyte, monitored over a time-period; feeding a trained neural network procedure with the monitored levels; and displaying, based on an output received from the procedure, a predicted level of the analyte in a future time. The procedure can comprise a plurality of layers, wherein for at least one pair of layers, a number of inter-layer connections within the pair is higher for later monitored levels than for earlier monitored levels.

Abstract: A method of treating atopic dermatitis (AD) in a subject in need thereof is provided. The method comprising administering to the subject a therapeutically effective amount of at least two species of bacteria.

Abstract: A method of predicting likelihood for gestational diabetes, comprises: obtaining a plurality of parameters characterizing a female subject, accessing a computer readable medium storing a machine learning procedure trained for predicting likelihoods for gestational diabetes, feeding the procedure with the plurality of parameters, and receiving from the procedure an output indicative of a likelihood that the subject has, or expected to develop, gestational diabetes, wherein the output indicative is related non-linearly to the parameters.

Abstract: A method of determining tolerance to an agent in a healthy subject is disclosed. The method comprises: (a) determining a signature of a microbiome in a sample of the healthy subject who has been subjected to the agent or condition; and (b) comparing the signature of the microbiome of the healthy subject to at least one reference signature of a pathological microbiome, wherein when the signature of the microbiome of the healthy subject is statistically significantly similar to the reference signature of the pathological microbiome, it is indicative that the healthy subject is intolerant to the agent.

Abstract: A method of predicting the quantity of a metabolite in the blood of a subject, accesses a computer readable medium storing a library of trained machine learning procedures, searches the library for a trained machine learning procedure associated with the metabolite, feeds the selected procedure with amount of a plurality of microbes of a microbiome of the subject, and receives from the selected procedure an output indicative of the quantity of the metabolite in the blood.

Abstract: A method of treating ALS in a subject in need thereof is disclosed. The method comprises administering to the subject a therapeutically effective amount at least two metabolites.

Abstract: A system for determining an approximate transformation between a first coordinate system and a second coordinate system, the system comprising a processing resource configured to: obtain an image captured by an image acquisition device of a mobile device; identify one or more synchronization objects within the image; determine first spatial dispositions of the synchronization objects with respect to a first coordinate-system origin of the first coordinate-system, the first coordinate system being a coordinate system of the mobile device; obtain information of second spatial dispositions of the synchronization objects with respect to a second coordinate-system origin of the second coordinate system; and determine, by employing an optimization scheme, utilizing the first spatial dispositions and the second spatial dispositions, the approximate transformation between the first coordinate-system and the second coordinate-system, the approximate transformation being usable by the mobile device for placing virtual

Abstract: A method of assessing whether a candidate subject is suitable for probiotic treatment is disclosed. The method comprises determining a signature of the gut microbiome of the candidate subject, wherein when the signature of the microbiome of the candidate subject is statistically significantly similar to a signature of a gut microbiome of a control subject known to be responsive to probiotic treatment, it is indicative that the subject is suitable for probiotic treatment.

Abstract: A method of analyzing the likelihood of weight regain in a subject who has reached a target weight by practicing a weight loss program is disclosed. The method comprises determining an amount or presence of at least one microbe and/or product thereof in the gut microbiome of the subject, wherein the amount of the at least one microbe is altered during a prior weight gain period of the subject to reach a level representative of an obese subject and further wherein the amount of the at least one microbe is retained at the level following the weight loss program, wherein the amount or presence of the at least one microbe or product thereof is predictive of weight regain.

Abstract: A system for generating approximately coordinated region maps (RM), the system comprising a processing resource configured to: provide a data repository comprising one or more RMs, each mapping a corresponding region, and each including information of a relative location of synchronization objects (SOs) located within the corresponding region with respect to a coordinate-system (CS) origin of a CS of the corresponding RM; obtain a given RM including information of relative locations of given SOs located within the given region with respect to a given CS origin of a given CS of the given RM; retrieve, from the data repository, reference RMs that meet a criteria; identify the reference RMs associated with at least one SO that match at least one of the given SO, giving rise to optimization RMs; and determine, utilizing an optimization scheme, an approximate transformation between the given CS and the CSs of the optimization RMs.

Abstract: A system for determining an approximate transformation between a first coordinate system and a second coordinate system, the system comprising a processing resource configured to: obtain an image captured by an image acquisition device of a mobile device; identify one or more synchronization objects within the image; determine first spatial dispositions of the synchronization objects with respect to a first coordinate-system origin of the first coordinate-system, the first coordinate system being a coordinate system of the mobile device; obtain information of second spatial dispositions of the synchronization objects with respect to a second coordinate-system origin of the second coordinate system; and determine, by employing an optimization scheme, utilizing the first spatial dispositions and the second spatial dispositions, the approximate transformation between the first coordinate-system and the second coordinate-system, the approximate transformation being usable by the mobile device for placing virtual

Abstract: Method of predicting a response of a subject to food is disclosed. The method comprises: selecting a food to which a response of the subject is unknown; accessing a first database having data describing the subject but not a response of the subject to the selected food; accessing a second database having data pertaining to responses of other subjects to foods, the responses of the other subjects including responses of at least one other subject to the selected food or a food similar to said selected food; and analyzing the databases based on the selected food to estimate the response of the subject to the selected food.

Abstract: Method of predicting a response of a subject to food is disclosed. The method comprises: selecting a food to which a response of the subject is unknown; accessing a first database having data describing the subject but not a response of the subject to the selected food; accessing a second database having data pertaining to responses of other subjects to foods, the responses of the other subjects including responses of at least one other subject to the selected food or a food similar to said selected food; and analyzing the databases based on the selected food to estimate the response of the subject to the selected food.

Abstract: A method of predicting likelihood for childhood obesity, comprises: obtaining a plurality of parameters, wherein at least a few of the parameters characterize an infant or toddler subject. A machine learning procedure trained for predicting likelihoods for childhood obesity is feed with the plurality of parameters. An output indicative of a likelihood that the infant or toddler subject is expected to develop childhood obesity is received from the procedure. The output is related non-linearly to the parameters.

Abstract: There is provided a method of diagnosing pathogenesis of viral infections for epidemic prevention, comprising: receiving a geographic location and responses to a questionnaire provided to undiagnosed persons, in each of iteration: inputting a first subset of answers and the geographical location of one of the undiagnosed persons into a geographic-level ML model component trained on a first training dataset including, for each subject: the first subset of answers, an indication of a certain geographic zone, and a label indicative of whether the respective subject is diagnosed or undiagnosed with the viral disease, inputting a second subset of the answers to a human-level ML model component trained on a second training dataset including, for each subject, the second subset of answers, and the label, and combining the outcome from the ML model components to calculate a combined likelihood of the respective undiagnosed person to be diagnosed with the viral disease.

Abstract: A method of improving the glucose response in glucose tolerant and intolerant subjects is provided. The method comprises providing to the subject probiotic compositions, or agents which specifically reduce bacterial species.