Artificial Intelligence has gotten a lot of attention recently, not just in healthcare but among most industries. Right along with it has been an increased focus on machine learning and its applications.
This blog post will discuss artificial intelligence and machine learning. It will explain the connection between these two concepts and how they apply in healthcare. Additionally, it will provide guidance on how your practice can prepare for their implementation. Let’s get started.
What is Artificial Intelligence & Machine Learning?
In a 2004 research paper, John McCarthy defines artificial intelligence as the creation of smart machines, specifically smart computer software. AI connects computers to comprehend human intelligence. However, it does not solely rely on biological methods.
IBM says artificial intelligence combines computer science and datasets to solve problems. Essentially, artificial intelligence mirrors human intelligence processes using machines, particularly computers.
Machine learning is a part of computer science and artificial intelligence. It uses algorithms and data to imitate human learning and get better with time. Computer systems are created to learn from data and make predictions and decisions without needing to be specifically programmed. Machine learning algorithms improve with time, becoming more accurate and effective as they analyze more data.
How do Artificial Intelligence & Machine Learning fit into healthcare?
AI and machine learning are often used in healthcare in various ways. First, healthcare professionals use AI and machine learning to develop self-monitoring, dynamic, auto-updating clinical risk prediction models. Traditional risk prediction is static and doesn’t update over time. With AI and machine learning, risk prediction is dynamic, taking evolving factors into account.
AI and machine learning in healthcare also utilize natural language processing. With natural language processing (NLP), a computer is able to understand, analyze, and create human language. You can use this to pull patient data from a doctor’s notes in order to quickly access information and help with decision-making.
How can you prepare your practice for Artificial Intelligence & Machine Learning?
Getting ready for AI and machine learning in your practice means improving your existing data processes. First, make sure clinicians and other professionals in your organization who create data understand the importance of information governance. Use clinical documentation improvement initiatives to improve the quality of data as it comes in.
Next, prevent the development of data siloes by investing in open, standards-based infrastructure to store data. Also, improve accountability and extend the usability of datasets by making sure all data assets include appropriate metadata. Finally, protect patients from unauthorized uses of information by maintaining high standards for data security and privacy.
Artificial intelligence and machine learning are already making a significant impact in healthcare, despite sounding futuristic. At Henry Schein MicroMD, we strive to offer solutions that help practices benefit from technological advancements.
From our robust MicroMD Practice Management and our simple, customizable, connected MicroMD EMR, to our incredible suite of Solutions Central partners, we are prepared to help you begin to bring the power of AI and machine learning into your practice.
To learn more, visit micromd.com or call 1-800-624-8832.
About the author,
Crystal Stanton
Crystal is a Digital Marketing Specialist at Henry Schein MicroMD. Content creation, social media management, and SEO optimization are just a few of her areas of concentration as she seeks to educate clients and prospects alike about the simple, customizable, and connected solutions we offer at MicroMD.
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