From Buzz to Reality: AI Integration in Healthcare Revenue Cycle Management
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From Buzz to Reality: Curtis Mayse shares expertise on navigating challenges and leveraging technology to optimize healthcare operations.
lukeciviello
- Feb 27
- 2 min
Unlocking Healthcare Efficiency: The Role of AI in Streamlining Coding Processes
Unlocking Healthcare Efficiency: Angela Opalak's insights on AI for medical coding, driving operational excellence.
Kyle Swarts
- Jan 11
- 2 min
Status Quo is the Biggest Impediment to AI Adoption
Despite the buzz, healthcare practices remain relatively hindered by the industry's status quo mentality.
aiHealth
- Oct 24, 2023
- 2 min
Navigating the Evolution of Medical Coding
Why Autonomous Medical Coding (AMC) is different from Computer-Assisted Coding (CAC)
aiHealth
- Sep 12, 2023
- 6 min
The Future of Medical Coding: Perspectives on Implementing Artificial Intelligence
Cynthia Sherman CCS-P, CHC, discusses the integration of Artificial Intelligence technology and medical coding practices.
aiHealth
- Jun 5, 2023
- 3 min
Reimagining Physician Compensation: A Two-Road Strategy
Ancore Health's CEO Eric Passon speaks about their two-road strategy for developing physician compensation plans.
aiHealth
- Mar 16, 2023
- 3 min
Applied AI: The Practical Use of Autonomous Coding
With over 30 years of experience in Revenue Cycle Management Koha Health’s CEO, Brian Hall, discusses how inefficient and manual RCM...
aiHealth
- Oct 19, 2022
- 3 min
Delivering Transparency and Accuracy to Medical Coding Using AI/ML
In our latest Q&A, aiHealth's Chief Technology Officer, Dave Wesley, talks about the launch of aiH.Automate™.
aiHealth
- Sep 26, 2022
- 5 min
The Next Generation of Medical Coding
We've taken the time to interview one of our founders and board members, Jean Balgrosky PH.D., MPH, RHIA about aiHealth’s vision.
Maxine Wesley
- Jun 30, 2022
- 2 min
AI Solutions for Equality in Healthcare - The Symbiosis Between Human and Machine
AI within healthcare can have the benefit of eliminating extra human errors or biases when processing patient data.
Maxine Wesley
- Mar 30, 2022
- 2 min
Explainability and Transparency in AI: Trusting the Process
Explainability is a characteristic that allows for the ‘behind the scenes’ of an AI system to be understood by a person.
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