Atrium — A Reference Model Context Protocol Server for FHIR Clinical Data with SMART-on ...
研究者らは、大規模言語モデル(LLM)が電子カルテの臨床データを活用するための基盤として、「Atrium」というオープンソースの参照モデルコンテキストプロトコル(MCP)サーバーを提案した。これはFHIR R4エンドポイントを公開し、SMART-on-FHIR認証を通じて安全にデータアクセスを可能にする。
3,748 FHIR-related articles (latest first)
研究者らは、大規模言語モデル(LLM)が電子カルテの臨床データを活用するための基盤として、「Atrium」というオープンソースの参照モデルコンテキストプロトコル(MCP)サーバーを提案した。これはFHIR R4エンドポイントを公開し、SMART-on-FHIR認証を通じて安全にデータアクセスを可能にする。
Telstra Health is tackling the problem of siloed medical data by implementing its AI-powered platform, 'Corus,' which utilizes the FHIR standard. This aims to centralize patient data across multiple providers and environments, thereby enhancing continuity of care.
The Taiwan Biomedical Equipment Industry Association, in collaboration with institutions like ITRI (Industrial Technology Research Institute), has established the 'AI Smart Healthcare Data Platform.' This platform uses FHIR (Fast Healthcare Interoperability Resources) as its core international standard to standardize and integrate medical data, aiming to significantly accelerate the development and validation process for AI-powered medical products.
This article addresses the challenges of traditional static Clinical Decision Support Systems (CDSS) within multi-site U.S. healthcare groups, such as functional fragmentation and difficulty integrating heterogeneous systems. It proposes a comprehensive implementation roadmap based on socio-technical integration to guide AI utilization.
This article presents a practical architecture demonstrating how to extract clinical and operational data from Epic EHR's FHIR format. It details using .NET and Azure Data Factory (ADF) to process the data into near real-time dashboards viewable via Power BI, specifically addressing API rate limit constraints.
Tech giants like Apple and Google are shifting their focus from hardware to 'medical compliance' in healthcare. Different regulatory environments are emerging globally, exemplified by the US FDA's approach versus strict regulations like the EU AI Act. Taiwan is establishing clear pathways for ICT industry entry into clinical systems through promoting FHIR standards.
Oracle Health has published the FHIR API endpoint specifications for the Specimen resource within its AI application suite. This specification defines how specimen information—used for diagnostic and environmental testing—is collected, maintained, and processed, encouraging developers to begin implementation in anticipation of production availability.
アイルランドのiEHRが、社会経済的決定要因(SDOH)に関する「Prapare Panel Example 93040-4」をFHIRリソースとして具体的に定義した。これは、観察結果(Observation)形式で、特定の質問票回答に基づく健康状態の記録方法を示す。
台湾の医材公会と工研院が共同で、スマート医療データプラットフォームを立ち上げた。本プラットフォームは、標準化された多岐にわたる医療データを集約し、生成AIを活用した新薬開発や診断支援システムの開発を加速させることを目的とする。
Based on a Nature paper, the autonomous medical AI agent 'MIRA' was developed. This system demonstrated its ability to autonomously execute an entire workflow—from patient history taking to diagnosis, testing, and treatment planning—within an EHR sandbox environment.
In this episode, Mike O'Neill, CEO of MedicaSoft, discusses how ACOs can move beyond mere data collection to generate real-time, actionable insights. He focuses on the role of FHIR, interoperability, and data strategy in supporting value-based care (VBC), aiming to improve care quality and operational efficiency.
Dicom Systems offers the cloud-based 'Unifier Medical Image Workflow Cloud Appliance' to enhance interoperability and manage complex image workflows in healthcare organizations. The product supports major protocols like DICOM, HL7, and FHIR, enabling flexible deployment from on-premises to cloud environments.
This article explains how to add 'Extensions' to resources and data types within the FHIR standard. It demonstrates the procedure for appending custom data, such as place of birth or date of birth, to a Patient instance by supplementing standard information.
FitsPro utilizes an HL7-compliant FHIR data model to ensure high compatibility with existing systems. This allows for the bidirectional exchange of patient information and diagnostic results in a standardized format.
Yuan-Rong Hospital showcased its self-developed 'Intelligent Provider Order Entry System (APOE)' at a Ministry of Health and Welfare organized exhibition. The system uses AI to generate preliminary medical records from consultation content, significantly improving physician efficiency.
The Indian government is building an integrated digital health ecosystem through the Ayushman Bharat Digital Mission (ABDM). This allows patients, hospitals, and insurers to securely exchange information using common standards, improving continuity and efficiency in healthcare.
MedX has announced a system that quantifies skin conditions, which previously relied on visual inspection and subjective judgment. This technology non-invasively measures three components—melanin, hemoglobin, and collagen—aiming to integrate objective data into electronic health records.
Yuanrong Medical System showcased its self-developed 'Intelligent Provider Order Entry (APOE)' system at the 'Great South AI Smart Health Exhibition.' The system utilizes AI to instantly identify consultation content and generate preliminary medical records, significantly improving clinical efficiency while maintaining quality control.
This article focuses on the U.S. Office of National Coordinator for Health IT's (ONC) proposed relaxation of regulations regarding 'Health Data, Technology, and Interoperability.' It systematically discusses three core elements: generative AI, FHIR standardized APIs, and healthcare system interoperability. Based on this, the author proposes a layered technical architecture for an IAM interoperable smart grid and a four-dimensional domain governance system, presenting a comprehensive roadmap for future medical digital transformation.
Rustで構築された「Helix」は、EMR記録やウェアラブルデータなど多様な個人データを単一の知識グラフに集約し、対話型分析を提供する。回答はユーザー自身のデータに基づき追跡可能であり、信頼性の高い情報提供を目指す。