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JMIR AI
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JMIR AI is a new peer-reviewed journal focused on research and applications for the health artificial intelligence (AI) community. It includes contemporary developments as well as historical examples, with an emphasis on sound methodological evaluations of AI techniques and authoritative analyses. It is intended to be the main source of reliable information for health informatics professionals to learn about how AI techniques can be applied and evaluated.
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Features
- Publishes original research articles, reviews, and editorials on the application of AI in health settings
- Provides a forum for the discussion of methodological issues in AI research
- Disseminates information on the latest AI technologies and their potential impact on health care
- Offers continuing education opportunities for health informatics professionals
- Promotes collaboration between researchers, clinicians, and industry partners
Advantages
- Provides a comprehensive overview of the latest research and applications of AI in health care
- Offers a rigorous peer-review process to ensure the quality of published articles
- Is indexed in PubMed Central and PubMed, making it easily accessible to researchers and clinicians
- Is open access, making it free to read and download for anyone with an internet connection
- Has a team of experienced editors and reviewers who are experts in the field of AI and health care
Disadvantages
- May not be suitable for readers who are not familiar with the field of AI
- May not cover all aspects of AI in health care
- May not be updated as frequently as some other journals
Frequently Asked Questions
-
Q:What is the scope of JMIR AI?
A:JMIR AI publishes original research articles, reviews, and editorials on the application of AI in health settings. This includes contemporary developments as well as historical examples, with an emphasis on sound methodological evaluations of AI techniques and authoritative analyses. -
Q:Who is the target audience for JMIR AI?
A:JMIR AI is intended for health informatics professionals, researchers, clinicians, and industry partners who are interested in the application of AI in health care. -
Q:How often is JMIR AI published?
A:JMIR AI is published quarterly. -
Q:Is JMIR AI open access?
A:Yes, JMIR AI is open access, which means that all articles are freely available to read and download. -
Q:How can I submit an article to JMIR AI?
A:Instructions for submitting an article to JMIR AI can be found on the journal's website.
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JMIR AI is a new peer-reviewed journal focused on research and applications for the health artificial intelligence (AI) community. It includes contemporary developments as well as historical examples, with an emphasis on sound methodological evaluations of AI techniques and authoritative analyses. It is intended to be the main source of reliable information for health informatics professionals to learn about how AI techniques can be applied and evaluated.
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fal.ai
fal.ai is a generative media platform designed for developers to build the next generation of creativity. It offers lightning-fast inference, access to high-quality generative media models, and optimization by the fal Inference Engine™. Developers can fine-tune their own models, leverage the fastest AI inference engine for diffusion models, and benefit from the best LoRA trainer in the industry for FLUX. The platform provides a world-class developer experience and cost-effective scalability based on actual usage.
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Raman Labs
Raman Labs is an AI tool that offers dedicated modules for computer vision-based tasks, allowing users to integrate machine learning functionality into their existing applications with just 2 lines of code. The tool provides real-time performance, simplicity, robustness to large scale and resolution variations, versatility, and adaptability to different computing power levels. It supports various platforms, hardware, and language integrations, with more coming soon. Raman Labs prioritizes user privacy by storing only email and hashed passwords, and all payment-related information is handled by a PCI DSS compliant service. The tool is licensed for personal use and can be run on multiple personal devices.
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LiteLLM
LiteLLM is a platform that provides model access, logging, and usage tracking across various LLMs in the OpenAI format. It offers features such as control over model access, budget tracking, pass-through endpoints for migration, OpenAI-compatible API access, and a self-serve portal for key management. LiteLLM also offers different pricing tiers, including Open Source, Enterprise Basic, and Enterprise Premium, with various integrations and features tailored for different user needs.