Abstract: Methods for assisting medical personnel in performing a diagnosis, diagnostic aids and computer readable media. The method initialisation step comprises: receiving a plurality of input medical texts tagged with potential medical codes; curating and validating the plurality of input medical texts to output a subset of medical texts that are validated and tagged with medical codes; and using the subset of tagged and validated medical texts to model the associations between the medical texts and the medical codes, and generating a medical text learning model based on the associations. The method diagnostic step comprises: inputting a specimen text relating to a patient into the medical text learning model; processing the specimen text using the medical text learning model; identifying suggested medical codes based on the specimen text; and outputting diagnoses, symptoms and treatments linked to the suggested medical codes for assisting medical personnel in providing a diagnosis for the patient.

Abstract: A method of training a neural network as a natural language processing, NLP, model, comprises: inputting annotated training data to first architecture portions of the neural network, the first architecture portions being executed respectively in a plurality of distributed client computing devices in communication with a server computing device, the training data being derived from text data private to the client computing device in which the first architecture portion is executed, the server computing device having no access to any of the private text data; deriving from the training data, using the first architecture portions, weight matrices of numeric weights which are decoupled from the private text data; concatenating the weight matrices, in a second architecture portion of the neural network executed in the server computing device, to obtain a single concatenated weight matrix; and training, on the second architecture portion, the NLP model using the concatenated weight matrix.

Abstract: A computer apparatus to identify healthcare resources used by a patient given a potential diagnosis, the apparatus comprising: a memory storing instructions for execution by a processor, the processor configured by the instructions to implement an impact estimator to: receive a patient clinical object, PCO, which represents the patient in the form of a graph, and includes previous healthcare resource utilization, HCRU, information of the patient as a patient HCRU subgraph; receive an HCRU knowledge graph, HCRU KG, associating healthcare resources with medical services; receive potential diagnosis information from a clinician; identify and extract potential healthcare resources and services in the HCRU KG associated with the potential diagnosis to form an HCRU subgraph associated with the potential diagnosis; and to perform graph analysis on the HCRU subgraph associated with the potential diagnosis and the patient HCRU subgraph to obtain an updated patient HCRU subgraph taking the potential diagnosis into acco

Abstract: A computer apparatus to identify healthcare resources used by a medical institution, comprising: a memory storing instructions for execution by a processor, the processor configured by the instructions to provide: a knowledge graph builder; and a knowledge graph customizer; wherein: the knowledge graph builder is arranged to input open data and clinician information, to generate a set of medical services terms and a set of medical resources terms from the open data and clinician information, and to associate the medical resources with the medical services to build a knowledge graph; and the knowledge graph customizer is arranged to match the knowledge graph with records of the medical institution to provide a customized subgraph of the knowledge graph which is specific to the medical institution.

Abstract: An array of registered entity property-value pairs representing a registered entity are stored in a data storage system. Each of the pairs includes a property label representing a property and a value range of the property. For each identifier property-value, an identifier property label, uniquely identifying the registered entity, and an identifier value representing a value of the identifier property are stored. A dataset is acquired with dataset property-value pairs for each of a first set of acquired dataset entities, where each pair includes a property label representing a property and a value representing a value range of the property. An identifier property-value pair matching an acquired dataset property-value pair for the acquired dataset entity is identified and then the acquired dataset property-value pairs are consolidated into the array of registered entity property-value pairs.

Abstract: Methods for assisting medical personnel in performing a diagnosis, diagnostic aids and computer readable media comprising code which, when executed by a computer, cause the computer to execute a method for assisting medical personnel in performing a diagnosis, the method comprising an initialisation step and a diagnostic step, wherein the initialisation step comprises: receiving a plurality of input medical texts tagged with potential medical codes; curating and validating the plurality of input medical texts to output a subset of medical texts that are validated and tagged with medical codes; and using the subset of tagged and validated medical texts to model the associations between the medical texts and the medical codes, and generating a medical text learning model based on the associations, and wherein the diagnostic step comprises: inputting a specimen text relating to a patient into the medical text learning model; processing the specimen text using the medical text learning model; identifying suggeste

Abstract: Diagnostic aids, methods for assisting medical personnel in performing a diagnosis, and computer readable media comprising code which, when executed by a computer, cause the computer to execute a method for assisting medical personnel in performing a diagnosis, wherein the diagnostic aids comprise: a receiver to receive an unstructured input; an analyser and parser to split the unstructured input into a plurality of logical components, and to detect medical terms in the plurality of logical components; a mapping engine to receive a medical classification hierarchy of medical standard codes in the form of a knowledge graph, and semantically annotate the knowledge graph with synonyms of medical terms used in the medical standard codes; an automatic coding solver to analyse the medical terms detected in the plurality of logical components by the analyser and parser, to generate a list of potential matching medical standard codes for each of the medical terms, to compare the lists of potential matching medical st

Abstract: A data storage system a process including: storing an array of registered entity property-value pairs representing the registered entity where each of the pairs includes a property label representing a property and a value range of the property; storing an entry of one identifier property-value pair where each pair includes an identifier property label uniquely identifying the registered entity, and an identifier value representing a value of the identifier property; acquiring a dataset having acquired dataset property-value pairs for each of a first set of acquired dataset entities, where each pair includes a property label representing a property and a value representing a value range of the property; identifying an identifier property-value pair matching an acquired dataset property-value pair for the acquired dataset entity; and consolidating the acquired dataset property-value pairs into the array of registered entity property-value pairs.

Abstract: An apparatus, method and program for generating a multiple-event pattern query for use in the retrieval of event information. The apparatus comprises: an inputter to receive an input query from a user; a retriever to analyze the received input query, and to retrieve an event query template from an event template database on the basis of the analysis; a pattern query formulation unit to receive the retrieved event query template, and to modify the event query template using the received input query to formulate the multiple-event pattern query; and a transmitter to transmit the multiple-event pattern query to an event information source, such that events matching the multiple-event pattern query may be identified.

Abstract: An event learner using machine intelligence includes an inputter to receive sample event patterns; an information retriever to retrieve terms information and to identify entities and predicates from the terms information; and a comparator to compare the identified entities and predicates against the sample event patterns, to generate a plurality of refined event patterns using the identified entities and predicates and the sample event patterns. An event extractor includes a selector to select raw information from a plurality of heterogeneous sources; a reformatter to identify entities and predicates in the raw information, and to generate reformatted information indicating the entities and predicates; and an analyser to analyse the reformatted information using the plurality of refined event patterns and, when an event matching a refined event pattern is identified, to store the event.

Abstract: An apparatus, method and program categorizing extracted events using a plurality of refined event patterns, and storing events matching a pattern in event storage; retrieving that match a pattern from the storage, to identify entities in the events, an event time of occurrence, and determine if events relate to the same occurrence, if the reconciliation determines that events relate to the same occurrence, reconciling the events retaining only a single event relating to an occurrence; receiving a query from a user, to reformat the query into a multiple-event pattern query, and semantically annotating the retained events, such that no information from the plural stored events relating to the same occurrence is lost, and receiving the pattern query to identify events matching the pattern query, and storing the events as a multiple event query response in a multiple event storage.

Abstract: A computer apparatus to identify healthcare resources used by a patient given a potential diagnosis, the apparatus comprising: a memory storing instructions for execution by a processor, the processor configured by the instructions to implement an impact estimator to: receive a patient clinical object, PCO, which represents the patient in the form of a graph, and includes previous healthcare resource utilization, HCRU, information of the patient as a patient HCRU subgraph; receive an HCRU knowledge graph, HCRU KG, associating healthcare resources with medical services; receive potential diagnosis information from a clinician; identify and extract potential healthcare resources and services in the HCRU KG associated with the potential diagnosis to form an HCRU subgraph associated with the potential diagnosis; and to perform graph analysis on the HCRU subgraph associated with the potential diagnosis and the patient HCRU subgraph to obtain an updated patient HCRU subgraph taking the potential diagnosis into acco

Abstract: A computer apparatus to identify healthcare resources used by a medical institution, comprising: a memory storing instructions for execution by a processor, the processor configured by the instructions to provide: a knowledge graph builder; and a knowledge graph customizer; wherein: the knowledge graph builder is arranged to input open data and clinician information, to generate a set of medical services terms and a set of medical resources terms from the open data and clinician information, and to associate the medical resources with the medical services to build a knowledge graph; and the knowledge graph customizer is arranged to match the knowledge graph with records of the medical institution to provide a customized subgraph of the knowledge graph which is specific to the medical institution.