When most people think about artificial intelligence (AI) and its applications, they tend not to think about its link to sleep and sleep health. The truth is, though, that AI is at the forefront of providing insights into what is and isn’t working for humans and their sleep. During an interview with Dr. Thomas Penzel, Chair of the Sleep Medicine Lab in Berlin, we uncovered the role of artificial intelligence in sleep medicine, its history, and what’s expected in the future.
The History of Artificial Intelligence in Sleep
Dr. Penzel has forty years of top-notch medical and scientific expertise and has been at the forefront of sleep medicine research for the last 15 years. During his extensive career, he has seen a transformation in how artificial intelligence has been used to generate meaningful sleep insights.
Early in Dr. Penzel’s career, AI was primarily used to diagnose sleep stages and then provide scores to these various stages. Over the years, AI has progressed to find extensive information about sleep disruption events like sleep apnea and leg cramps. These sleep events have the potential to negatively affect the quality of sleep for millions of people around the world.
More recently, there has been a move towards passive and nondisruptive data collection. This means that what happens in the sleep lab more closely mirrors what happens in the real world. According to Dr. Penzel, being equipped with more accurate information about what is disrupting sleep helps doctors to implement meaningful treatment programs.
The Different Types of AI
Dr. Penzel acknowledges that AI is focused on the broad goal of looking at challenging issues and regularly updating information and expectations to determine the likelihood of an event occurring. Yet, despite these broad similarities, he notes that it is crucial to recognize that there is a wide range of different AI tools. For instance, there is machine learning, big data analysis, and data trees. Due to technological innovations, though, machine learning tends to make up a disproportionate share of AI innovations. In fact, many people use the terms AI and machine learning interchangeably.
The Terminology Used in AI
During the interview, Dr. Penzel mentioned that consumers often use “artificial intelligence” as a broad umbrella term. However, there are important terms that both patients and doctors should be aware of. One of the most important terms is trustworthy AI. According to Dr. Penzel and others, trustworthy AI is AI where we have faith in the generated outcomes and can use it to inform patient care. This does not mean that we blindly trust AI conclusions, however. Human verification is still a necessary component.
The Limitations of AI Data
One of the most significant controversies in the field of AI, as it relates to sleep, is what happens when a human who is reading a sleep study and an AI tool disagree about a sleep event. Dr. Penzel highlighted that in past years there was a tendency to try to determine which of the two was wrong: the person or the machine. It was seen as a binary choice.
Today, he notes that there is more of a willingness to see these events as shades of gray. For example, it’s possible that AI technology may be better suited to identify certain sleep apnea symptoms. In comparison, a human with years of clinical experience may be better skilled at picking up on different types of subtleties. In the real world, these shades of gray and nuance are positive and will ultimately generate better patient care than in the previous black-and-white world.
Dr. Penzel also noted another significant limitation of AI: it tries to smooth the average. This means that AI may not be as well-equipped to deal with a unique patient or an outlier. These rare cases would then also have to be excluded from system updates. Simply put, AI does well with things that are within the bounds of what has been seen before but struggles with the unusual or one-offs.
The Importance of Data Quality in AI
Today, artificial intelligence is being used in an ever-increasing number of medical situations. Dr. Penzel highlighted how critical it could be to guide treatment protocols in intensive care units. For example, AI can quickly analyze bloodwork and urine results more objectively than traditional doctors’ analyses.
However, Dr. Penzel also notes that an information gap exists too. People do not understand exactly what AI is, and they are concerned about whether the information generated by AI is trustworthy. Dr. Penzel contends that AI is largely trustworthy, but it hinges on the quality of the inputs. Poor quality inputs will never generate strong outcomes, no matter how good the technological tool is.
It’s more important now than ever before that the data used in AI is accurate and consistent. Poor data inputs will not provide the precise information needed to learn more about sleep and improve health outcomes.
The Future: Where Sleep and AI Intersect
The future of medicine, according to Dr. Penzel, is a future that will incorporate AI into a wide variety of specialties, ranging from oncology to sleep medicine. This is primarily because of how fast AI is. It can create a tremendous amount of information quickly, and it also controls for and mitigates the impact of human errors.
But AI is not perfect. It also has numerous downsides, based on Dr. Penzel’s analysis, including a lack of understanding of what AI really is. This means that the best medical solutions will happen when AI cutting-edge technology is combined with the input of highly skilled medical professionals.
To learn more about sleep medicine from a trusted source for improving sleep, visit www.healthiersleepmag.org.
Jessica Thomas is a public health professional, health & wellness writer, and entrepreneur. She enjoys learning about and educating others on healthy living and observing how technology is changing the healthcare space.
References
University of Copenhagen Faculty of Science. Artificial intelligence enhances efficacy of sleep disorder treatments. ScienceDaily. 8 June 2021. www.sciencedaily.com/releases/2021/06/210608113257.htm
Ducharme J. A Third of Americans Are Sleep-Deprived. This Technology Could Help Them Rest Easier. Time. January 25, 2019. https://time.com/5494363/sleep-artificial-intelligence/
Goldstein CA, Berry RB, Kent DT, et al. Artificial intelligence in sleep medicine: background and implications for clinicians. J Clin Sleep Med. 2020;16(4):609-618. doi:10.5664/jcsm.8388
