Augmented intelligence (AI), often called artificial intelligence, holds great potential and physicians appreciate this. An AMA survey of more than 1,000 doctors found that nearly two-thirds can see AI’s potential benefits.
A CME series featured on the AMA Ed Hub™ introduces learners to foundational principles in AI and machine learning, a subdomain of AI that enables computers to learn patterns and relationships from data without being explicitly programmed by people. Developed by the AMA ChangeMedEd initiative and the University of Michigan DATA-MD team and geared toward medical students, it is also suitable for residents, fellows, practicing physicians and other health professionals.
The third module in the series, “The Use of AI in Diagnosis,” explores how AI-based diagnostic tools can complement physicians’ diagnostic decision-making.
The AMA has developed new advocacy principles that build on current AI policy. These new principles (PDF) address the development, deployment and use of health care AI. Meanwhile, AMA Ed Hub also features a 16-credit CME course on artificial and augmented intelligence in health care.
Look before you leap
Each AI system has its limitations, and physicians must have the skills necessary to identify those limitations, the module notes.
“These skills include critically evaluating diagnostic studies of systems that use AI/ML before implementing those systems in their clinical practice, just as they would any intervention that may impact patient care,” it says.
Using a hypothetical clinical case of a physician considering whether to use an ML model to screen a patient for diabetic retinopathy based on a real-world study of a deep-learning algorithm for detection of diabetic retinopathy in retinal fundus photographs, the module lays out how to perform the evaluation.
For starters, when reviewing studies of machine learning-based diagnostic tools, physicians should ask themselves:
- What are the results of the study?
- Are the results of the study valid?
- Will the results help me care for my patients?
From AI implementation to EHR adoption and usability, the AMA is making technology work for physicians, ensuring that it is an asset to physicians—not a burden.
Learn more with the AMA about the emerging landscape of augmented intelligence in health care (PDF).
Learn from those who have done it
Each of these questions has corresponding follow-up questions. For example, to answer, “Will the results help me care for my patients?” physicians should consider the following:
- Will the reproducibility of the test result and its interpretation be satisfactory in my setting?
- Are the results applicable to my patient?
- Will the results change my patient management?
- Will patients be better off as a result of the test?
The module then provides sample answers to each.
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Looking specifically at a study published in JAMA, the module says of the question of reproducibility:
“We cannot draw any definitive conclusions here. However, it is possible that the test results and interpretation would be reproducible. The algorithm’s performance may vary when applied to images from different image systems and patient populations not included in the development and validation sets. External validation in our setting would allow us to be more confident when using the model if its performance is similar to its performance during development.”
Periodic knowledge checks and review sections test the user’s vocabulary and their understanding of how concepts are applied.
The CME module “The Use of AI in Diagnosis” is enduring material and designated by the AMA for a maximum of 0.50 AMA PRA Category 1 Credit™.
It is part of the AMA Ed Hub, an online platform with high-quality CME and education that supports the professional development needs of physicians and other health professionals. With topics relevant to you, it also offers an easy, streamlined way to find, take, track and report educational activities.
Learn more about AMA CME accreditation.
