Abstract: A classification code parser and method can include: reading a classification code having a description; reading a required keyword, and a total number of keywords associated with the classification code; reading text of a note; tokenizing the text of the note to create a note token stream, the note token stream having a note token and a position of the note token within the note token stream; creating a keyword map including a total number of matched keywords; determining a match ratio from the total number of the matched keywords and the total number of the keywords; determining a proximity factor based on a shortest span of tokens within the note token stream containing all the matched keywords; and determining a strength of a match between the classification code and the note based on the match ratio being multiplied by the proximity factor.

Abstract: A computer-implemented method for sharing access to a database of records relating to clinical trial investigators amongst a number of users is disclosed. Each record includes a number of data fields associated with a clinical trial investigator and has associated metadata indicating a record owner. The method comprises: a) receiving a database query from a first user; b) resolving the query using a first subset of the records in the database including only those records for which the associated metadata indicates that the record owner is the first user and those records for which the associated metadata indicates that the record owner is another user which has registered a sharing rule in respect of the first user, whereby the first user is granted permission to access its records; and c) generating a result set including only those records used to resolve the query that satisfy the query.

Abstract: A method includes ingesting, by a clinical trial management platform, data from multiple clinical trial site systems associated with multiple clinical trials, responsive to authentication of user credentials of a user, providing the user with access to the clinical trial management platform, based on the user credentials, identifying a particular clinical trial associated with the user, through the clinical trial management platform, providing the user with access to multiple clinical trial software services based on the authenticated user credentials, based on the ingested data for the particular clinical trial associated with the user, presenting to the user a user-specific task list for user tasks related to the particular clinical trial; and through the clinical trial management platform, establishing a communication link between the user and another user, the communication link enabling direct, real-time messaging via the clinical trial management platform between the user and the other user.

Abstract: A computer-assisted method including obtaining healthcare records from multiple different data sources that each provide information regarding a corresponding type of healthcare events, identifying healthcare records from the multiple different data sources that are for a healthcare event associated with a particular individual and that occurred during a particular period of time, and generating a composite record for the particular individual for the particular period of time, and storing the composite record in a database of composite records. The composite record include an identifier for the particular individual, a pharmaceutical transactions array, where each entry in the pharmaceutical transactions array represents a pharmaceutical transaction that occurred during the particular period of time, and a medical visit array, where each entry in the medical visit array represents a medical visit that occurred during the particular period of time.

Abstract: Methods and systems to train and use an ensemble of artificial intelligence/machine learning (AI/ML) models to extract information from social determinants of health (SDoH), including training each of multiple dimensionality reduction models to reduce dimensionality of socio-demographic variables associated with a respective one of multiple SDoH categories, training a predictive model to predict a patient behavior for a geographic region (e.g., risk of non-adherence to treatment regimens) based on dimensionally reduced SDoH (alone or in combination with selected socio-demographic variables and/or other data), training a patient classification model to classify patients based on prescription transactions, and/or training a regional similarity model to determine a measure of similarity between geographic regions based on SDoH and/or dimensionally reduced SDoH. Also disclosed are techniques to visually represent outputs of the models on a user-interactive display.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a heterogenous network and determining diffusion weights of scientific evidence in the heterogenous network. The computer obtains clinical data associated with a clinical network of healthcare providers and scientific data associated with a scientific network of scientists. The computer generates a first graph network representing the clinical network and a second graph network representing the scientific network. The computer identifies a first set of target nodes in the first graph network representing clinical leaders, and a second set of target nodes in the second graph network representing scientific leaders. The computer predicts links connecting the first graph network to the second graph network and generates a heterogenous network with nodes from the first graph network and from the second graph network, and the links connecting the first graph network to the second graph network.

Abstract: Methods and systems including computer programs encoded on computer storage media, for a method for detecting signals related to subjects participating in a clinical trial. In some implementations, a computer collects clinical data from multiple sources. The computer standardizes and redacts personally identifiable information and determines predictive features that correspond to characteristics of the data that correlate with efficacy and safety signals. The computer obtains training data and trains machine learning models to predict one or both of a predicted efficacy signal and a predicted safety signal for a subject. The computer receives clinical data for a particular clinical trial subject enrolled in an ongoing clinical trial and predicts one or more signals and receives a review of the signals through a user interface. The computer updates the predictive components of the system based on the review.

Abstract: A method and system obtain records for a health care provider from sources, each record specifying an address for the health care provider. An accuracy score to each address is assigned based on (i) relationships among some of the records for the health care provider or (ii) applicability, to the address, of an accuracy trend for the source of the address. The accuracy score for each of the addresses is adjusted based on applying audit rules to the address, each audit rule specifying an adjustment to the accuracy score based on a value in the record for the address satisfying or violating the audit rule. The addresses for the health care provider and rankings are stored. A ranking for an address is determined based on the relative adjusted accuracy scores of the address. Data indicative of the address rankings can be displayed on a user interface.

Abstract: Methods and systems to identify collaborative communities of individuals from graphs of multiple types of relationships amongst the individuals, including to mine data related to multiple types of relationships amongst individuals, construct graphs to represent the respective types of relationships amongst individuals, and perform a multiplex graph convolutional network (MGCN) artificial intelligence machine learning (AIML) analysis across the multiple graphs to identify the collaborative communities. A mathematical representation of the graphs may be learned/tuned to optimize clustering of the individuals. Multiple parameters (inter-graph weights, consensus regularization function) may be jointly tuned based on a joint optimization function. The collaborative communities may be displayed such that relative positions of the individuals represent measures of influence exerted by the respective individuals within the respective collaborative communities.

Abstract: Some implementations provide a computer-implemented method for identifying, from on-line postings, reports of potential adverse effects resulting from consuming a healthcare product, the method including: receiving a log of on-line postings regarding consuming the healthcare product; receiving a database comprising a healthcare taxonomy and a set of linguistic rules; analyzing, based on the healthcare taxonomy, the log of on-line postings to identify a report of at least one adverse effect resulting from consuming the healthcare product; generating a score for the identified report according to the healthcare taxonomy and the set of linguistic rules; comparing the generated score with a threshold; and in response to determining that the generated score is above the threshold, flagging the identified report as a report of a potential adverse effect.

Abstract: A method of managing consent using a computing device, the consent is given by a subject to one or more events in one or more studies, wherein the consent and the plurality of activities are changeable, the method including: authoring one or more first data forms describing the one or more events and one or more selections responsive to the one or more events; authoring, for each of the plurality of subjects, one or more second data forms including description of a plurality of preferences; forming, for a first of the plurality of subjects, an Informed Consent Forms document by combining the one or more first data forms of a first of the one or more studies and one or more second data forms for the first subject; and generating a manifest indicating the one or more events in the first study to which the first subject has granted consent.

Abstract: A method is described that includes receiving a request to translate source content from a first language to a second language. The method includes processing the source content to generate first anonymized content by automatically anonymizing confidential information in the source content. The method also includes providing the first anonymized content to a first service provider to provide anonymization input and processing the first anonymized content with the anonymization input to generate second anonymized content. The method further includes obtaining a machine translation of the second anonymized content from the first language to the second language and providing the machine translation to a second service provider to provide translation input. The method further includes processing the machine translation with the translation input to generate translated content.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for creating source-specific, persistent patient identifiers for healthcare service providers. One method includes accessing a record of healthcare data, wherein the record includes patient identifying information (PII) associated with one or more persons to whom the healthcare data pertains. The portions of PII included in the accessed record of healthcare data are extracted from the accessed record and encrypted. Based on one or more business rules, one or more hashed tokens are created by applying one or more hashing functions to the extracted portions of PII. A source-specific identifier is received, the source-specific identifier having been encoded in a manner specific to an organization associated with the computer system and having been encoded with reference to the one or more hashed tokens. An association is stored between the source-specific identifier and the accessed record of healthcare data.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating an execution plan for a request that involves accessing and synthesizing data assets from siloed data repositories. In one aspect, a method comprises receiving a first request, generating a request execution plan comprising (i) a sequence of second requests and (ii) a respective indicator of a relationship between a corresponding response for each second request and an overall response to the first request by processing the first request using a request planner artificial intelligence (AI) neural network agent, sequentially, assigning and providing each second request in the sequence of second requests to a particular retriever AI neural network agent in accordance with metadata corresponding with a particular data repository, obtaining the corresponding response to the second request, and generating the overall response to the first request using a synthesizer AI neural network agent.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for creating source-specific, persistent patient identifiers for healthcare service providers. One method includes accessing a record of healthcare data, wherein the record includes patient identifying information (PII) associated with one or more persons to whom the healthcare data pertains. The portions of PII included in the accessed record of healthcare data are extracted from the accessed record and encrypted. Based on one or more business rules, one or more hashed tokens are created by applying one or more hashing functions to the extracted portions of PII. A source-specific identifier is received, the source-specific identifier having been encoded in a manner specific to an organization associated with the computer system and having been encoded with reference to the one or more hashed tokens. An association is stored between the source-specific identifier and the accessed record of healthcare data.

Abstract: Cohort definition and selection system for a computer having a memory, a central processing unit and a display, the system including: a cohort definition module to configure the memory according to a phenotype vector. The phenotype vector includes a patient ID to uniquely associate the phenotype vector to a patient, a plurality of demographic dimension fields, each demographic dimension field to describe a respective demographic aspect of the patient, a calculated dimension field to describe a calculated information related to the patient, a plurality of phenotype-based dimension fields, each phenotype-based dimension field to indicate relevance of the respective phenotype-based dimension field to the patient, and a child phenotype vector to recursively define a phenotype-based dimension field, and a cohort selection module to select a set of phenotype vectors that are within a predetermined error from a cohort selection criteria.

Abstract: Systems, methods, devices, and non-transitory, computer-readable storage media are disclosed for matching a service requester with a service provider via a taxonomy based directed graph. The method includes: receiving a keyword associated with a service; accessing a directed graph including a root node and nodes connected by edges, each node having a title; identifying a second node of the directed graph for each of service providers, each second node having a title matching a skill of a respective service provider; determining a distance between the first node and each second node along the directed graph; and ranking the service providers based at least in part on the distance between the first node and each second node. Systems, methods, devices, and non-transitory, computer-readable storage media are further disclosed for determining and storing a quality score for the revised linguistic content.

Abstract: Embodiments of the present disclosure provide a method for monitoring/tracking the lifecycle of a drug from build (e.g., as part of clinical trial development), to approval (e.g., regulatory), to in-market (e.g., distribution and safety information). The use of artificial intelligence (AI) and blockchain technology may enable the system to track the drug down to the prescription level and may support a digital label that can be updated as necessary based on such monitoring (e.g., that can be amended based on safety information detected while the drug is in market and warnings sent out upon amendment).

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for responding to a query. In some implementations, a computer obtains a query. The computer determines a meaning for each term in the query. The computer determines user data for the user that submitted the query. The computer identifies one or more ontologies based on the meanings for at least some of the terms. The computer identifies a knowledge graph based on the identified ontologies and the user data. The computer generates a response to the query by traversing a path of the identified knowledge graph to identify items in the knowledge graph based on the determined meaning for each of the terms. The computer generates path data that represents the path taken by the computer through the identified knowledge graph. The computer provides the generated response and the path data to the client device.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for creating source-specific, persistent patient identifiers for healthcare service providers. One method includes accessing a record of healthcare data, wherein the record includes patient identifying information (PII) associated with one or more persons to whom the healthcare data pertains. The portions of PII included in the accessed record of healthcare data are extracted from the accessed record and encrypted. Based on one or more business rules, one or more hashed tokens are created by applying one or more hashing functions to the extracted portions of PII. A source-specific identifier is received, the source-specific identifier having been encoded in a manner specific to an organization associated with the computer system and having been encoded with reference to the one or more hashed tokens. An association is stored between the source-specific identifier and the accessed record of healthcare data.