How AI has evolved in healthcare: From pilot to scale

Over two decades, the author has observed the evolution of AI, transitioning from the challenges of the "AI Winter" to the current advancements in large language models (LLMs). At Ensemble, a leading revenue cycle management company, the focus is on enhancing LLMs through neuro-symbolic AI, which combines intuitive language processing with structured logic. This hybrid approach addresses LLM limitations, particularly in healthcare, where compliance and accuracy are critical. Ensemble's strategy involves high-fidelity data sets, collaboration with domain experts, and elite AI scientists to develop effective AI solutions. Successful applications include improving clinical reasoning for denial appeals, enhancing reimbursement processes, and streamlining patient engagement, ultimately aiming to deliver meaningful impact in healthcare through rigorous and responsible AI deployment.

🧬 Clinical data registries hold massive potential — and AI can help unlock it. Nilesh Chandra, Steve Carnall, Erik Moen, and Nori Horvitz outline a guided approach to applying AI in registries, ensuring accuracy, scalability, and meaningful insights. With the right guardrails, AI can transform registries from static repositories into engines of discovery and care improvement. 🚀 The future of registries isn’t just storage — it’s intelligence in action. Read more: https://lnkd.in/dNzJYCYf #HealthDataManagement #AIinHealthcare #ClinicalData #HealthInnovation

🧬 Clinical data registries hold massive potential — and AI can help unlock it. Nilesh Chandra, Steve Carnall, Erik Moen, and Nori Horvitz outline a guided approach to applying AI in registries, ensuring accuracy, scalability, and meaningful insights. With the right guardrails, AI can transform registries from static repositories into engines of discovery and care improvement. 🚀 The future of registries isn’t just storage — it’s intelligence in action. Read more: https://lnkd.in/dNzJYCYf #HealthDataManagement #AIinHealthcare #ClinicalData #HealthInnovation

Modern CDM vs. Traditional CDM The role of Clinical Data Management is evolving rapidly. What once relied heavily on manual processes is now being transformed by AI and Data Science. 👉 For today’s CDM professionals, these are not just “good-to-have” skills — they’re the must-have capabilities that will define the future of the field. Learn AI in Clinical Trials: https://lnkd.in/gqCyGWCW Learn Clinical Data Science: https://lnkd.in/gWSEJXkV #ClinicalDataManagement #AI #DataScience #FutureSkills #ClinicalResearch

Successful AI vendors recognize that even the best technology must fit into a highly human-centered and often unpredictable environment. https://ow.ly/hGxo50WRo4E

Successful AI vendors recognize that even the best technology must fit into a highly human-centered and often unpredictable environment. https://ow.ly/CC7H50WQrcM

Successful AI vendors recognize that even the best technology must fit into a highly human-centered and often unpredictable environment. https://ow.ly/332t50WQrlS

Successful AI vendors recognize that even the best technology must fit into a highly human-centered and often unpredictable environment. https://ow.ly/Y5A050WQG1e

As humans move from using AI for prediction to using it to produce content, the opportunities are vast. The downside of using AI for creative pursuits is homogeneous production. https://lnkd.in/e9wTst6p

The foundation of AI in healthcare is high-quality clinical data - DOTmed: Data quality is the best predicator of AI success. It is crucial to recognize that, for all the hype, AI is fundamentally a branch of Machine ...