Center for Telehealth and eHealth Law (CTeL)’s Post

🔥 Lots of incredible AI models being released this week and increased attention on how AI can help in the most important ways. - Firstly, I loved watching Prashant Natarajan testify before the US #Congress on his perspective and work related to #veteransaffairs. https://lnkd.in/g6ecn_db - Secondly, on the heels of completely overhauling #bard with #gemini , Google DeepMind has released Gemini 1.5. This model looks extremely promising as another compute-efficient multimodal model that supports up to 10M token context length (!!). The needle-in-a-haystack testing of this model looks excellent. https://lnkd.in/gkFt_bAZ - Thirdly, more models are coming out related to text-to-video. #openai has released #sora a model that can produce text-to-video up to about a minute. I know very little about this model currently, but it's part of a growing trend. Organizations that aren't locked into to a single AI vendor are the only ones that can truly benefit from the incredible advancements we're seeing happen before our eyes.

Artificial Intelligence has great potential to help the health sector concerning prevention, diagnosis, treatment, and even reducing administrative tasks for overburdened health workers. Developing country health systems face major challenges in taking advantage of this new technology, but it can be done. All of the above are discussed in detail in an article co-authored by Dr. Ok Pannenborg and Richard Seifman, which is found in the link below: (https://lnkd.in/eBhjvUfH)

Just published! A very interesting document by Pan American Health Organization about the use of #AI in #PublicHealth and I find valuable the guiding principles of use among other topics I hope to review and comment later. I like the #Ethics of those statements: 1. People-centered: This principle emphasizes the importance of placing individuals at the forefront of AI interventions, ensuring that actions and solutions prioritize the well-being and rights of each person involved. 2. Ethically grounded: This principle underscores the necessity of aligning discussions, developments, and implementations with globally recognized ethical principles such as human dignity, beneficence, nonmaleficence, and justice, to ensure ethical considerations guide AI applications in public health. 3. Transparent: Transparency is a key principle, emphasizing the need to develop AI algorithms using clear and open approaches that are communicated effectively, allowing stakeholders to understand the processes and outcomes involved. 4. Data-protected: This principle highlights the critical importance of prioritizing privacy, confidentiality, and data security in all stages of AI development to safeguard sensitive health information and maintain trust in AI-enabled public health initiatives. 5. Demonstrates scientific integrity: AI interventions should adhere to robust scientific standards, including reliability, reproducibility, fairness, honesty, and accountability, to ensure credibility, accuracy, and effectiveness in public health applications. 6. Open and shareable: This principle promotes openness and sharing of tools and concepts in AI development, emphasizing the value of transparency, collaboration, and the accessibility of AI technologies to foster innovation and progress in public health. 7. Nondiscriminatory: This principle emphasizes the need for fairness, equality, and inclusiveness in the impact and design of AI interventions, highlighting the importance of mitigating biases and ensuring equitable access to healthcare resources and services. 8. Human-controlled technology: This principle advocates for formal processes that enable human oversight and review of automated decisions made by AI systems, ensuring accountability, oversight, and ethical governance in the use of AI for public health initiatives.  If you like to get a copy of this reference tool, just click below and like always, like & share of this feed will be greatly appreciated.

AI Transforming Health Care: Trust, Equity, and Policy Source: KP ''Current use of AI How and where is AI being used in health care? What are the benefits of AI for patients, clinicians, and the health system? The future What new developments are on the horizon, and what advantages could AI bring? What risks do we face, as AI rapidly expands? How can we build trust and incorporate health equity into AI design and implementation? How can we mitigate risks while harnessing benefits, and what is the role of public policy?'' Watch the videos: https://lnkd.in/eZb-aCdM

Did you know that currently, some 4.5 billion people lack access to essential healthcare services? It's a staggering number, but there's hope. Detailed data can help identify and address gaps in healthcare provision, while machine learning and artificial intelligence can help with disease detection and precision therapies. Let's work together to ensure everyone has access to the healthcare they need. #Healthcare #Data #AI #ML

Here is a striking new report from ICF on the top trends shaping government this year. We're seeing many of these challenges across public health agencies, particularly the underutilization of data for decision-making. Download the full report to learn more. https://lnkd.in/eBNjAFdm

A new issue of the North Carolina Medical Journal is live today. Sean Sylvia, Associate Professor in the Department of Health Policy and Management at UNC Gillings School of Global Public Health, served as guest editor, bringing the complex and complicated issue of #ArtificialIntelligence (#AI) home to the work and lives of North Carolina researchers, clinicians, and policymakers. https://lnkd.in/eMnb3NAk Articles in this issue answer questions such as: 🤔 Can AI improve electronic health records? 🤫 What are the privacy implications of using AI at the clinical level? 🚫 What do people mean when they talk about “bias” in AI? 👩⚕️ How will AI impact our health workforce?

Public willingness to share health data is revolutionising trials. Companies can embrace AI and data transparency for faster, more adaptive research. Find out how my colleagues are doing this in this article. #ClinicalResearch #DataPrivacy #AI

Check out “Demystifying AI Tools in Health Care: An Introduction for Federal Policymakers” including my presentation with Lynn Shapiro Snyder hosted by the Alliance for Health Policy as part of their annual Signature Series. Learn about key concepts, the current legislative and regulatory landscape, AI’s impact on health care stakeholders, current risks and pitfalls of AI tools, and risk mitigation strategies. Watch the full webinar here: