Abstract: This technology automates assessment of real-estate property assets by aggregating a heterogeneous dataset of stored online asset reviews for one or more property assets based on one or more search criteria. Next, labeling of a subset of the aggregated heterogeneous dataset in one or more pre-defined property asset problem categories with one or more labeler computing devices is managed. One or more machine learning models are trained in text classification based on the labelled subset and another unlabeled subset of the heterogeneous dataset of stored online asset reviews. The trained one or more machine learning models in text classification are executed on the heterogeneous dataset of stored online asset reviews to calculate a category assessment score in each of the pre-defined property asset problem categories.

Abstract: A method for identifying cancer driver genes is provided. The method includes receiving at least one patient input file containing information for a mutation variation and/or an expression of the gene, parsing the information from the input file into a data structure, annotating the information with cancer driving related annotation, extracting genetic features related to the patient from the information, and scoring the information with a first probability that the mutation variation drives cancer and/or a set of further probabilities that the expression of the gene drives cancer. The first probability and the set of further probabilities are calculated with a first and second Bayesian Network graphical model, respectively.

Abstract: A method comprising using at least one hardware processor for: computing a tree edit distance between two medical treatment plans; and displaying an output based on the computed tree edit distance. The two medical treatment plans are optionally a recommended treatment plan and an executed treatment plan. The output is optionally indicative of compliance of the executed treatment plan with the recommended treatment plan.

Abstract: Machines, systems and methods for supporting clinical decisions comprises providing a graphical user interface (GUI) to facilitate selection of one or more treatment plans (TPs) for one or more clinical presentations (CPs), wherein data records for the TPs and the CPs are implemented over a data structure that defines one or more relationship between the CPs and the TPs, according to medical guidelines or clinical data, wherein interaction with the GUI allows for filtering through TPs associated with one or more CPs, or filtering through CPs associated with one or more TPs, wherein selecting a CP from among a plurality of the CPs results in display of one or more TPs associated with the selected CP, and wherein cross-referencing between results displayed in response to the selection of the selected CP and TP provides details that help determine one or more relevant TPs for a target CP.