Math&Maroc’s Post

Abstract This research paper investigates the emerging role of Generative Artificial Intelligence (Generative AI) within health information systems. With a focus on its applications in data processing, diagnostics and patient care, analytics and its impact on improving the quality of healthcare services, challenges and future perspectives of the integration of Generative AI in healthcare. Through a comprehensive exploration, this study contributes to the growing discourse on the use of advanced technologies to improve health services and health information management and overall patient outcomes. Generative AI has emerged as a transformative technology in the field of health information systems, providing innovative solutions and capabilities. This paper explores the key role of generative AI in improving healthcare data processing, facilitating diagnostics and revolutionizing patient care. Through an in-depth analysis, we aim to shed light on the potential benefits, challenges and future implications of integrating Generative AI into health information systems. https://lnkd.in/gjqsr6iy

Paul Evans was recently featured in a Business North Carolina article discussing the emerging impact of artificial intelligence on North Carolina's clinical research industry. As Paul notes, "Our industry is in the same place as most people with AI. We've seen a step change. Everybody started with efficiency gains, back-office functions. Then you move on to how you use AI to transform the industry." Under Paul's leadership — and with a technology hub in Hyderabad, India — Velocity Clinical Research continues to be at the forefront of innovation, navigating the complexities of AI integration while maintaining a rapid growth trajectory. With 90 sites across the U.S., U.K., Germany, and Poland, and a database of over 1 million patients, Velocity is poised to leverage AI for future advancements in clinical trials. Read the full article: https://lnkd.in/gEBxhvHt

Join the AI demo tomorrow!!!!

Did I just condense a Health AI webinar into a 7 minute clip? You be the judge. These are some of the highlights from our Challenges in Adopting AI into Clinical Workflows webinar. Many thanks to Ekanjali Dhillon, Eduard Dolynskyi, Anna Shahinyan, Andrew Harrison and Tanya Chib for sharing their expertise. Replay link in the comments. And while you're here why not register for our next webinar on Tuesday: Building Trust in Health AI: A Multidisciplinary Approach (also in the comments).

Using AI for public impact: Insights from Dr. Soroush Saghafian Read more about the five key takeaways from an AI pioneer about its potential impact in healthcare! 1. UNDERSTAND AND MITIGATE ALGORITHM AVERSION IN HEALTHCARE 2. BRIDGE AI SOLUTIONS AND PUBLIC POLICY 3. PROMOTE EQUITY THROUGH ETHICAL AI PRACTICES 4. OVERCOME REGULATORY AND IMPLEMENTATION CHALLENGES 5. THE FUTURE OF AI IN HEALTHCARE: PREDICTIVE AND PROACTIVE MODELS https://lnkd.in/ehn8xeWb

About 10% of #healthcare expenditure in the U.S. will be going to medical #AI. It will be a huge waste if we do not know how to use it correctly. In this interview with Fast Company, I discussed some of our findings and work on increasing the public impact of #AI. 👇👇👇

Just finished the course “An Introduction to How Generative AI Will Transform Healthcare”!

In today's fast-paced world, healthcare systems globally are grappling with unprecedented challenges. From staffing shortages to administrative burdens, the pressure on our healthcare providers has never been greater. But there's a beacon of hope on the horizon: Generative AI.Generative AI is revolutionizing the healthcare landscape by streamlining operations, enhancing diagnostic accuracy, and improving patient care. These advanced algorithms can analyze vast amounts of data, identify patterns, and generate insights that were previously unattainable. Learn more at:

AI in Healthcare: The Future is Bright, but Challenges Remain ⚖️💻 At the CCTSI CU-CSU Summit, Jayashree Kalpathy-Cramer, PhD, shed light on the vast potential of AI in healthcare. Here are my key takeaways: - Dr. Kalpathy-Cramer emphasized AI's ability to analyze large amounts of data, identify patterns, and predict patient outcomes. This could revolutionize medical decision-making and patient care. - However, she also highlighted the limitations of AI in healthcare, including the need for high-quality training data, addressing bias in algorithms, and ensuring transparency and explainability. In my opinion, we're just scratching the surface of AI's capabilities in healthcare. While there are challenges to overcome, the rewards will be well worth the effort. Subscribe to my AI Newsletter to stay up-to-date on the latest developments and insights: [AI Newsletter](https://lnkd.in/gRgPMgKc) 📱

Just finished the course “An Introduction to How Generative AI Will Transform Healthcare”! Check it out: https://lnkd.in/ej3GtaQ4