Search results for "FHIR": 1,661 articles
A research team developed a Machine Learning (ML)-based Clinical Decision Support System (CDSS) to aid in the early detection of sepsis. The system ensures interoperability and security by integrating with Electronic Health Record (EHR) data using standards like HL7 FHIR.
FHIR.sk has released a comprehensive toolkit for medical data exchange. This enables the creation, validation, and simulation of FHIR resources, allowing developers to build more advanced systems.
FHIR requires defining constraints (Profiles) for specific use cases and validating data against those constraints. This ensures structural and terminological integrity, enabling highly interoperable data exchange.
This article provides fundamental knowledge of modern healthcare interoperability, centered on FHIR (Fast Healthcare Interoperability Resources). It covers core concepts like REST API and Resource, alongside definitions of specific clinical resources such as Patient, Observation, and Condition.
This article explains the `$millis()` function within the data transformation language JSONata. This function is shown to return the number of milliseconds since the Unix Epoch (January 1, 1970 UTC) as a number. Basic usage and type checking methods are demonstrated.
本ページは、HL7 FHIRを基盤としたヨーロッパの医療情報交換（eHealth）に関する包括的な知識提供を行う。特にスロバキニアの国内状況から、EUレベルでのEHDS対応やGDPR準拠のための技術的指針が網羅されている。
A technical specification for HL7 FHIR's reference structure has been published. Specifically, it defines the set of codes common to two ValueSets: 'Referenced Item Category' and 'Document Class'. This provides foundational information for handling both referenced items and document classification in medical data.
A ValueSet is defined that contains the common codes from two different 'Participation Role Type' ValueSets. This provides a unified code system spanning multiple standard concepts.
Xziryは、サイロ化された医療データを抱える現場に対し、単一の統合レイヤーを提供します。これにより、EHRやPACSなどの既存システムとAIソリューションを安全かつ効率的に接続し、データ連携の複雑な課題を解決します。
Leading healthcare IT solutions provider Mindbowser announced its membership in HIMSS. This move strengthens its network with global healthcare leaders and innovators, focusing on improving data exchange and connectivity.
eHealth Infrastructure has released a specification (OperationDefinition) for transforming DK-HL7 Personal Health Monitoring Report (PHMR) XML documents into FHIR Observation resources. This enables the standardized handling of personal health monitoring data within electronic medical records.
The AJ FHIR Platform provides an open-source, integrated infrastructure compliant with HL7 FHIR R4/R5 standards. It offers multiple independent functions—including authentication, consent management, and EHR data access—to achieve secure healthcare interoperability.
InterSystems is hosting a technical webinar detailing how AI agents can access FHIR data in targeted ways, and the role of MCP in bridging Generative AI (GenAI) with data sources. The session will also cover integrating existing repositories into new use cases.
To operationalize AI healthcare products, 'interoperability quality' is essential beyond mere model development. Compliance with standards like HL7 v2 and FHIR ensures data pipeline reliability, which determines success in enterprise deployment.
The 'FHIR Fundamentals Course,' jointly organized by HL7 and AeHIN, successfully concluded in May 2026. Ninety-seven participants from 16 countries attended the course, contributing to foundational knowledge of health information exchange across the Asia-Pacific region.
eHealth Infrastructure has released an OperationDefinition providing statistical data on CarePlan status changes. This allows quantitative tracking of time spent and occurrences within various statuses, such as 'draft,' 'active,' and 'completed,' grouped by specific PlanDefinitions.
This article details the extension of the AI-powered FHIR patient data summarization tool, 'FHIR Patient Snapshot Agent.' The developer added source context vector search functionality and IRIS-compatible embedded Python artifacts, enhancing its utility as a clinical summarization prototype.
HiPaaSの「FHIRFlo」は、HL7やCCDAなど多様な形式の電子カルテデータやファイル（CSV, PDF等）をAIを用いて自動的にFHIR R4標準に変換します。これにより、臨床データを一元管理し、コンプライアンスを遵守したAPI経由でのセキュアなアクセスを実現することで、米国の規制対応を支援します。
This article explains the usage of various functions provided by FUME (FHIR Coverter). Specific methods are detailed, including ID retrieval functions like $resourceId() and $literal(), as well as $search() for executing queries against a server, and $resolve() for resolving references.
A research paper details the development and validation of an open data model aimed at achieving semantic interoperability in pharmacogenomics for clinical practice. The model integrates genetic and disease information, aiming for integration into electronic health records (EHR).