Navigating the AI Showcase at RSNA 2019: A Comprehensive Guide
Table of Contents
- Introduction
- The State of AI in Radiology
- Growth of AI in Radiology
- Funding and Regulatory Approval
- Navigating the AI Showcase at RSA 2019
- Overview of the AI Showcase
- Types of Companies Involved
- Traditional Vendors
- AI Startups
- Evaluating AI Vendors
- Questions to Ask AI Vendors
- Questions to Ask Platform Vendors
- Risk and Accuracy of AI
- Impact on Clinical Workflow
- Benefits of AI in Radiology
- Workflow Integration
- Technical Requirements
- Procuring and Deploying AI Solutions
- Cost and Licensing
- Vendor Stability and Long-term Support
- Network Requirements
- Interface with PACS
- Conclusion
Introduction
Welcome to the Black Lips evaluating AI and RS no 2019 webinar. Today, we will be discussing the state of AI in radiology and navigating the AI showcase at the RSA 2019 conference. We will also delve into the process of evaluating AI vendors and the impact of AI on clinical workflow. By the end of this article, you will have a comprehensive understanding of the current landscape of AI in radiology and how it can be integrated into your practice.
The State of AI in Radiology
Growth of AI in Radiology
Over the past few years, there has been a significant growth in the adoption of AI in radiology. In 2016, there were only a few medical application companies exhibiting at the RSA. However, in 2019, there will be a staggering 129 companies exhibiting at the AI showcase. This growth is also reflected in the amount of funding going into medical imaging AI startups, with $700 million invested in 50 deals last year.
Funding and Regulatory Approval
One key indicator of the maturing industry is the delivery of applications that have regulatory approval. Currently, there are 50 AI applications with FDA clearance. This increasing number of applications with regulatory approval demonstrates the utility and value proposition of AI in radiology. With these advancements, we can expect to see deployments in the field and the generation of revenue in the near future.
Navigating the AI Showcase at RSA 2019
Overview of the AI Showcase
The AI showcase at RSA 2019 is a platform where companies involved in AI in radiology can demonstrate their products and innovations. The showcase has seen significant growth over the years, with a wide range of companies from different regions participating. It is divided into two main categories: traditional vendors and AI startups.
Types of Companies Involved
There are two main types of companies involved in the AI showcase: traditional vendors and AI startups.
Traditional Vendors
Traditional vendors are established companies that already have products widely deployed in the market. They have a satellite booth within the AI showcase and are expanding their offerings to include AI solutions. These companies have the advantage of existing revenue streams and a well-established customer base.
AI Startups
AI startups are newer companies that are focused on developing AI solutions for specific conditions. These startups are typically smaller teams, often less than ten people, with a focus on specific areas of radiology. They are usually more specialized and offer innovative products that may not yet be widely adopted.
Evaluating AI Vendors
When evaluating AI vendors, it is essential to ask the right questions and consider various factors. Here are some questions to ask AI vendors:
- What is the regulatory status of your product?
- How accurate is your AI algorithm compared to radiologists?
- What is your workflow integration strategy?
- What are the technical requirements for implementing your solution?
Similarly, when evaluating platform vendors, consider asking the following questions:
- Can your platform support multiple AI vendors?
- How often are updates released, and how are they deployed?
- What are the licensing and billing arrangements?
- How stable and financially secure is your company?
It is crucial to understand the cost, technical aspects, and long-term support provided by vendors.
Impact on Clinical Workflow
AI technology has the potential to significantly impact the clinical workflow in radiology. It offers various benefits, including improved efficiency, faster diagnosis, and higher quality of care. However, it is essential to ensure that AI seamlessly integrates with existing workflows to minimize disruption.
Benefits of AI in Radiology
AI can enhance radiologists' efficiency by providing automated analysis and highlighting potential abnormalities. It allows radiologists to work faster, increase their volume, and provide better treatment plans. Additionally, AI can add value to referrals and improve patient care.
Workflow Integration
The success of AI implementation depends on how well it integrates into the clinical workflow. Ideally, AI reports and images should be readily accessible within the PACS system, minimizing the need for additional viewers or switching between applications. Workflow optimization is crucial to maximize the benefits of AI while minimizing any negative impact.
Technical Requirements
Deploying AI solutions requires careful consideration of technical requirements. It includes deciding whether to process data locally or in the cloud, network capabilities, and ensuring compliance with patient data protection regulations (HIPAA). Additionally, understanding the interface requirements between the PACS system and AI vendors is essential for seamless integration.
Procuring and Deploying AI Solutions
When procuring and deploying AI solutions, several factors need to be considered. These include cost, licensing, vendor stability, and the method of deployment.
Cost and Licensing
The cost of AI solutions varies, typically ranging from $1 to $3 per study. Most vendors offer subscription-based pricing models or operate on a pay-per-use basis. Licensing may differ based on the vendor, and agreements should be reviewed carefully to ensure compliance with legal and technical requirements.
Vendor Stability and Long-term Support
Vendor stability is essential when making long-term investments in AI solutions. It is crucial to choose vendors backed by venture capitalists, with a sustainable business model. Long-term support is also important, as updates and new releases are regularly introduced to improve the product's performance and address any issues.
Method of Deployment
Deciding between on-site deployment or using cloud-based solutions depends on specific requirements. Both options have their advantages and challenges, including considerations of data privacy (PHI) and network speed and reliability. It is crucial to assess these factors and choose the deployment method that aligns with your organization's needs.
Conclusion
AI technology is transforming radiology, offering potential benefits such as improved efficiency, accuracy, and patient care. However, successfully navigating the AI landscape requires careful evaluation of vendors, understanding workflow integration, and considering technical requirements. By selecting the right AI solutions and effectively integrating them into existing workflows, radiologists, hospitals, and imaging centers can harness the full potential of AI in radiology.
If you would like to explore AI solutions further or need guidance in selecting the right vendor, the Blackford Platform offers a curated marketplace of imaging applications and a robust infrastructure for deploying AI solutions. We remain committed to helping you leverage AI technologies to enhance clinical practice.
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