BackgroundRecent advances in Artificial Intelligence (AI) are changing the medical world, and AI will likely replace many of the actions performed by medical professionals. The overall clinical ability of the AI has b...
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BackgroundRecent advances in Artificial Intelligence (AI) are changing the medical world, and AI will likely replace many of the actions performed by medical professionals. The overall clinical ability of the AI has been evaluated by its ability to answer a text-based national medical examination. This study uniquely assesses the performance of Open AI's ChatGPT against all Japanese National Medical Licensing Examination (NMLE), including images, illustrations, and *** obtained the questions of the past six years of the NMLE (112th to 117th) from the Japanese Ministry of Health, Labour and Welfare website. We converted them to JavaScript Object Notation (JSON) format. We created an application programming interface (API) to output correct answers using GPT-4 for questions without images and GPT4-V(ision) or GPT4 console for questions with *** percentage of image questions was 723/2400 (30.1%) over the past six years. In all years, GPT-4/4V exceeded the minimum score the examinee should score. In total, over the six years, the percentage of correct answers for basic medical knowledge questions was 665/905 (73.5%);for clinical knowledge questions, 1143/1531 (74.7%);and for image questions 497/723 (68.7%), *** medical knowledge, GPT-4/4V met the minimum criteria regardless of whether the questions included images, illustrations, and pictures. Our study sheds light on the potential utility of AI in medical education.
Objective Interest in application programming interfaces (APIs) is increasing as key stakeholders look for technical solutions to interoperability challenges. We explored three thematic areas to assess the current sta...
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Objective Interest in application programming interfaces (APIs) is increasing as key stakeholders look for technical solutions to interoperability challenges. We explored three thematic areas to assess the current state of API use for data access and exchange in health care: (1) API use cases and standards;(2) challenges and facilitators for read and write capabilities;and (3) outlook for development of write capabilities. Methods We employed four methods: (1) literature review;(2) expert interviews with 13 API stakeholders;(3) review of electronic health record (EHR) app galleries;and (4) a technical expert panel. We used an eight-dimension sociotechnical model to organize our findings. Results The API ecosystem is complicated and cuts across five of the eight sociotechnical model dimensions: (1) app marketplaces support a range of use cases, the majority of which target providers' needs, with far fewer supporting patient access to data;(2) current focus on read APIs with limited use of write APIs;(3) where standards are used, they are largely Fast Healthcare Interoperability Resources (FHIR);(4) FHIR-based APIs support exchange of electronic health information within the common clinical data set;and (5) validating external data and data sources for clinical decision making creates challenges to provider workflows. Conclusion While the use of APIs in health care is increasing rapidly, it is still in the pilot stages. We identified five key issues with implications for the continued advancement of API use: (1) a robust normative FHIR standard;(2) expansion of the common clinical data set to other data elements;(3) enhanced support for write implementation;(4) data provenance rules;and (5) data governance rules. Thus, while APIs are being touted as a solution to interoperability challenges, they remain an emerging technology that is only one piece of a multipronged approach to data access and use.
Metaproteomics, the study of collective proteomes in environmental communities, plays a crucial role in understanding microbial functionalities affecting ecosystems and human health. Pathway analysis offers structured...
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Metaproteomics, the study of collective proteomes in environmental communities, plays a crucial role in understanding microbial functionalities affecting ecosystems and human health. Pathway analysis offers structured insights into the biochemical processes within these communities. However, no existing tool effectively combines pathway analysis with peptide- or protein-level data. We here introduce PathwayPilot, a web-based application designed to improve metaproteomic data analysis by integrating pathway analysis with peptide- and protein-level data, filling a critical gap in current metaproteomics bioinformatics tools. By allowing users to compare functional annotations across different samples or multiple organisms within a sample, PathwayPilot provides valuable insights into microbial functions. In the re-analysis of a study examining the effects of caloric restriction on gut microbiota, the tool successfully identified shifts in enzyme expressions linked to short-chain fatty acid biosynthesis, aligning with its original findings. PathwayPilot's user-friendly interface and robust capabilities make it a significant advancement in metaproteomics, with the potential for widespread application in microbial ecology and health sciences. All code is open source under the Apache2 license and is available at https://***.
Objectives This study sought to capture current digital health company experiences integrating with electronic health records (EHRs), given new federally regulated standards-based application programming interface (AP...
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Objectives This study sought to capture current digital health company experiences integrating with electronic health records (EHRs), given new federally regulated standards-based application programming interface (API) *** and methods We developed and fielded a survey among companies that develop solutions enabling human interaction with an EHR API. The survey was developed by the University of California San Francisco in collaboration with the Office of the National Coordinator for Health Information Technology, the California Health Care Foundation, and ScaleHealth. The instrument contained questions pertaining to experiences with API integrations, barriers faced during API integrations, and API-relevant policy *** About 73% of companies reported current or previous use of a standards-based EHR API in production. About 57% of respondents indicated using both standards-based and proprietary APIs to integrate with an EHR, and 24% worked about equally with both APIs. Most companies reported use of the Fast Healthcare Interoperability Resources standard. Companies reported that standards-based APIs required on average less burden than proprietary APIs to establish and maintain. However, companies face barriers to adopting standards-based APIs, including high fees, lack of realistic clinical testing data, and lack of data elements of interest or *** The industry is moving toward the use of standardized APIs to streamline data exchange, with a majority of digital health companies using standards-based APIs to integrate with EHRs. However, barriers *** A large portion of digital health companies use standards-based APIs to interoperate with EHRs. Continuing to improve the resources for digital health companies to find, test, connect, and use these APIs "without special effort" will be crucial to ensure future technology robustness and durability.
Clinical decision support tools for risk prediction are readily available, but typically require workflow interruptions and manual data entry so are rarely used. Due to new data interoperability standards for electron...
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Clinical decision support tools for risk prediction are readily available, but typically require workflow interruptions and manual data entry so are rarely used. Due to new data interoperability standards for electronic health records (EHRs), other options are available. As a clinical case study, we sought to build a scalable, web-based system that would automate calculation of kidney failure risk and display clinical decision support to users in primary care practices. We developed a single-page application, web server, database, and application programming interface to calculate and display kidney failure risk. Data were extracted from the EHR using the Consolidated Clinical Document Architecture interoperability standard for Continuity of Care Documents (CCDs). EHR users were presented with a noninterruptive alert on the patient's summary screen and a hyperlink to details and recommendations provided through a web application. Clinic schedules and CCDs were retrieved using existing application programming interfaces to the EHR, and we provided a clinical decision support hyperlink to the EHR as a service. We debugged a series of terminology and technical issues. The application was validated with data from 255 patients and subsequently deployed to 10 primary care clinics where, over the course of 1 year, 569 533 CCD documents were processed. We validated the use of interoperable documents and open-source components to develop a low-cost tool for automated clinical decision support. Since Consolidated Clinical Document Architecture-based data extraction extends to any certified EHR, this demonstrates a successful modular approach to clinical decision support.
application programming interfaces (APIs) have become prevalent in today's software systems and services. APIs are basically a technical means to realize the co-operation between software systems or services. Whil...
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ISBN:
(纸本)9783030860448;9783030860431
application programming interfaces (APIs) have become prevalent in today's software systems and services. APIs are basically a technical means to realize the co-operation between software systems or services. While there are several guidelines for API development, the actually applied practices and challenges are less clear. To better understand the state of the practice of API development and management in the industry, we conducted a descriptive case study in four Finnish software companies: two consultancy companies developing software for their customers, and two companies developing their software products. As a result, we identified five different usage scenarios for APIs and emphasize that diversity of usage should be taken into account more explicitly especially in research. API development and technical management are well supported by the existing tools and technologies especially available from the cloud technology. This leaves as the main challenge the selection of the right technology from the existing technology stack. Documentation and usability are practical issues to be considered and often less rigorously addressed. However, understanding what kind of API management model to apply for the business context appears as the major challenge. We also suggest considering APIs more clearly a separate concern in the product management with specific practices, such as API roadmapping.
This work is part of the effort to develop a speech recognition system for Brazilian Portuguese. The resources for the training and test stages of this system, such as corpora, pronunciation dictionary, language and a...
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ISBN:
(纸本)9783642123191
This work is part of the effort to develop a speech recognition system for Brazilian Portuguese. The resources for the training and test stages of this system, such as corpora, pronunciation dictionary, language and acoustic models, are publicly available. Here, an application programming interface is proposed in order to facilitate using the open-source Julius speech decoder. Performance tests are presented, comparing the developed systems with a commercial software.
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