Keith Neal, MBA, MHL, CHFP, CRCR’s Post

#AI was the top tech trend of 2023, but 2024 is when we’ll really begin to feel AI’s impact on healthcare. I had a great chat with Charlie King from Healthcare Digital, where we talked about what that impact will look like, as well as some critical challenges to AI adoption that cannot be ignored. https://lnkd.in/eQQjEHq4

This article from Healthcare IT News discusses Cleveland Clinic's approach to leveraging artificial intelligence (AI) in healthcare. It highlights the importance of building a strong data foundation, creating a data and AI innovation ecosystem, and democratizing innovation to engage with industry innovators and accelerate outcomes. Cleveland Clinic emphasizes the need for upskilling talent and a generational change in how organizations deliver services. The piece further mentions the ethical considerations of AI applications, with Cleveland Clinic's AI Taskforce evaluating algorithms for quality, ethics, and bias to mitigate health disparities and ensure responsible AI use. https://lnkd.in/e6qP99-3 #healthcare #healthcareai #aiethics #healthcareit #healthcaredata #healthcareinnovation

A recent ABBYY study reveals that 57% of global healthcare providers fear falling behind without adopting AI. Efficiency, patient service, and staying competitive are key motivators. Yet, trust in AI lags behind other industries, with concerns around data reliability and misuse. Despite these hurdles, AI budgets are growing, and healthcare leaders see potential in tools like Large Language Models (LLMs) and intelligent document processing. But with only 53% having formal AI ethics policies, the industry has work ahead! https://lnkd.in/eTSN9h2x #HealthcareAI #Innovation #AIAdoption

70% of life sciences experts acknowledge AI's potential, but many struggle with its implementation at scale, due to challenges like data wrangling, trustworthiness of AI, and lack of user-friendly tools according to this article from Technology Networks. (https://lnkd.in/e29xBtTi) Few tools on the market can tackle multiple challenges simultaneously, but Cerbrec #Graphbook is an exception. As a graphical deep learning framework, it uniquely addresses these issues at once, providing a singular solution for life sciences researchers to overcome the hurdles working with #GenAI models. #Graphbook not only harmonizes fragmented data from diverse sources and automates data processing to elevate data wrangling, but also simplifies AI model development with an intuitive point-and-click interface, empowering life sciences researchers to build trustworthy AI models. By providing visibility and intelligent guidance, our platform can greatly enhance productivity and expedite discovery for life sciences researchers. Send us an inquiry or book a demo by reaching us at [email protected] to learn how #Graphbook can help your research and development efforts! #SafeAI #ResponsibleAI #AiSecurity #AiAdoption #GenAI #Cerbrec

🌟 Exciting News! The EU Adopts New AI Act: What It Means for DIGESTAID - Digestive Artificial Intelligence Development 👉 The EU Parliament has recently adopted the landmark Artificial Intelligence Act, bringing significant changes to the AI landscape in Europe. Here's a breakdown of what will and won't change, and how DIGESTAID - Digestive Artificial Intelligence Development is positioned: 🔍 What Will Change? The AI Act introduces new regulations to ensure the ethical and responsible use of AI technologies. It sets clear rules for AI systems, including high-risk applications, transparency, accountability, and data privacy. 💼 What Won't Change? While the AI Act imposes stricter regulations, it also promotes innovation by providing a clear framework for AI development. It encourages responsible AI practices while fostering technological advancements. 👩💼 How Does It Look for DIGESTAID - Digestive Artificial Intelligence Development? As a leading AI healthcare company, DIGESTAID - Digestive Artificial Intelligence Development is already aligned with the principles outlined in the AI Act. Our focus on ethical AI, data privacy, and transparency ensures that our technologies meet the highest standards of compliance and responsibility. 💡 FAIR Data Principles Moreover, DIGESTAID - Digestive Artificial Intelligence Development datasets adhere to FAIR principles (Findable, Accessible, Interoperable, and Reusable), making our data infrastructure robust and compliant with the AI Act's emphasis on data governance. This ensures that our AI models and subsequently, technologies such as Deep Capsule, have access to high-quality, standardized data, driving innovation while protecting privacy. 🌐 Learn More: Read the full details of the EU's new AI Act: https://lnkd.in/gWyrXJCw 🚀 DIGESTAID - Digestive Artificial Intelligence Development is proud to lead the way in ethical AI for healthcare, ensuring a brighter, more responsible future for AI innovation. #DigestAId #AIAct #AIRegulation #HealthcareAI #EthicalAI #Innovation #Compliance #FAIRData

The EU AI Act has the potential to significantly impact the healthcare industry by ensuring the secure, ethical, and efficient use of artificial intelligence (AI) in medical contexts. The Act categorizes AI systems based on their potential impact on safety and fundamental rights, and establishes a regulatory framework that accounts for these risks. Healthcare providers and AI developers must carefully navigate these regulations to balance innovation with patient safety. Under the Act, AI systems that pose an intolerable risk to health, safety, or fundamental rights are prohibited from use in healthcare environments. High-risk AI systems that are classified as high risk must comply with strict regulatory requirements, including risk assessment procedures, adherence to data governance and quality standards, transparency requirements, resilient cybersecurity protocols, and human supervision. AI applications that have low or minimal risk are encouraged to adhere to established guidelines and voluntary ethical standards. Healthcare providers and AI developers must work together to ensure these technologies are utilized safely and transparently. The EU AI Act's regulatory framework has implications for the use of AI in healthcare, including the use of AI for diagnosing medical conditions, monitoring patients, providing treatment suggestions, and managing confidential health information. By guaranteeing the safe and ethical utilization of AI in healthcare, the EU AI Act has the potential to improve patient outcomes while promoting innovation in the field.

AI's ability to process vast data enhances diagnostic accuracy and personalized treatments, but it raises concerns about data privacy, algorithm biases, and the need for empathetic human care. Integrating AI within existing healthcare systems and balancing its role alongside healthcare professionals are key aspects to address. The evolution of AI in healthcare requires a combined effort involving ethical consideration, strategic planning, and adaptability to ensure its successful and responsible implementation. #Healthcare #ArtificialIntelligence #Data #Technology https://lnkd.in/ejG82WKQ

Sunday Select: Health AI Industry Standards Take Shape 📰 The Coalition for Health AI (CHAI), a diverse group of stakeholders in the healthcare industry focused on harmonized AI standards, released its draft framework for responsible health #AI. The framework includes an Assurance Standards Guide and an accompanying Assurance Reporting Checklist (ARC). ➡ The CHAI Assurance Standards Guide and ARC present the most comprehensive set of principles and #governance checklists to date. Importantly, the two documents align with several leading AI frameworks, including the White House Blueprint for an AI Bill of Rights, several frameworks from the National Institute of Standards and Technology (NIST), and the National Academy of Medicine’s (NAM’s) AI Code of Conduct work (among others). ➡ The Assurance Standards Guide takes the following five principles-based themes into consideration: (1) Usefulness, Usability, and Efficacy, (2) Fairness and Equity, (3) Safety and Reliability, (4) Transparency, Intelligibility, and Accountability (5) Security and Privacy. The Guide outlines CHAI's 6-Stage Lifecycle for Health AI Development and Deployment. The stages are (1) Define the Problem & Plan, (2) Design the AI System, (3) Engineer the AI Solution, (4) Assess the System, (5) Pilot the System, and (6) Deploy & Monitor the System. ➡ In parallel to the Assurance Standards Guide is the ARC, which spans four checkpoints: (1) Initial Planning, (2) Readiness for Real-World, (3) Real-World Impact and Full Deployment Readiness, and (4) Large Scale and Longer Terms Impacts. The four checkpoints are "intended to guide the development and evaluation of a complete AI solution and system against CHAI standards for trustworthy AI." ➡ #Developers and #deployers of health AI solutions face a shifting landscape of regulatory obligations at the federal and state level, patient safety and litigation risk, and an array of industry principles and standards guides. The CHAI documentation centers the conversation around AI governance processes calibrated for stakeholders in the healthcare industry and is a step toward consensus. ➡ In addition to internal governance and testing requirements, deployers and developers should be cognizant of the existing web of healthcare-specific regulations (e.g., FDA #SaMD implications). Moreover, developers and deployers face various considerations from a contracting perspective (e.g., larger organizations tend to place stringent AI-specific governance and testing obligations on vendors of AI services). Implementing an AI governance and assurance strategy is essential for mitigating risks, ensuring compliance, and fostering trust.💡 Rebecca E. Gwilt Carrie Nixon Michael Pappas Kaitlyn O'Connor LUKASZ KOWALCZYK MD Fabio Thiers, MD PhD Mandeep Maini, NACD.DC™ Jeffery Recker More info:

Excellent overview of the consequences of the new EU AI Act. It requires an internally implemented comprehensive oversight of AI systems, ensuring they adhere to legal requirements and ethical norms throughout their development, deployment, and use.

The EU AI Act aims to standardize #AI safety but faces criticism for its broad scope, potentially hindering innovation, especially in healthcare. Tailoring regulations to specific AI applications' risks is crucial to balance safety and innovation effectively. Read this article by our Senior Government Affairs Lead, Jess Ross, to learn more: https://bit.ly/3QvjdcZ