Artificial intelligence has made its way into drug development, surgery and medical advice — and now it’s helping people improve the quality of their sleep.
The Artificial Intelligence in Sleep Medicine Committee, which is part of the American Academy of Sleep Medicine, recently published a paper that highlights how AI is contributing to the field of sleep medicine.
The committee looked at how AI is assisting in three areas: clinical applications, lifestyle management and population health.
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Clinical applications involve the use of AI to diagnose and treat sleep disorders, while lifestyle management focuses on the use of consumer technology to track sleep data.
In the third area, population health, AI technology reveals a new approach to public health regarding sleep, according to Dr. Anuja Bandyopadhyay, chair of the Artificial Intelligence in Sleep Medicine Committee at Riley Children’s Hospital, Indiana University School of Medicine.
“Good quality and quantity of sleep is essential for good health,” Bandyopadhyay said in an interview with Fox News Digital.
“As sleep medicine doctors, we have been recommending that for years, but sleep is often the first thing to be sacrificed to make time for other competing interests.”
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For years, patients didn’t have access to tools to track their sleep or sleep habits, Bandyopadhyay said — which made it difficult for doctors to get the data they needed to assess the quality and quantity of sleep.
“With the advent of AI, we now have the ability to track sleep, identify patterns and recognize changes in other physiological parameters that can inform the clinician if something isn’t right,” she said.
“At the same time, this technology can help patients track their sleep and understand their sleep habits in a better way, empowering them to make positive changes for their own benefit.”
6 examples of AI in action for better sleep
Bandyopadhyay shared some specific examples of how AI can be used to help improve the quantity and quality of sleep.
No. 1 – Personalized sleep monitoring
“AI-powered devices can monitor sleep patterns more accurately through wearable technology and smart devices,” Bandyopadhyay told Fox News Digital.
“They can analyze data such as movement, heart rate and breathing to provide detailed insights into sleep quality.”
No. 2 – Sleep disorder diagnosis
AI algorithms can assist in diagnosing sleep disorders like insomnia, sleep apnea and narcolepsy by analyzing large datasets from sleep studies more efficiently than traditional methods, the expert noted.
No. 3 – Sleep recommendations
“AI can offer personalized sleep recommendations based on individual sleep patterns, lifestyles and health data,” Bandyopadhyay said.
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“This could include advice on sleep hygiene, optimal sleep times and relaxation techniques.”
No. 4 – Predictive analytics
AI can predict potential sleep issues by analyzing patterns and data trends, allowing people to take preventative measures before problems become severe.
No. 5 – Smart sleep environments
“AI can be integrated into smart home systems to create environments conducive to better sleep,” said Bandyopadhyay.
This might include recommendations for adjusting lighting, temperature and sound based on individual sleep cycles.
No. 6 – Mental health integration
“Given the strong link between sleep and mental health, AI can help by providing holistic health insights and integrating sleep data with mental health assessments to offer comprehensive wellness solutions,” said Bandyopadhyay.
Risks, limitations of using AI for sleep
While advances in AI technology have been shown to help humans optimize everyday tasks and functions, experts urge caution.
“It is still a complex algorithm that requires sufficient training and supervision,” Bandyopadhyay said.
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“It would be naive to assume that AI can be autonomous and replace clinical expertise.”
All sleep disorders are different, the expert noted, with differences in symptoms and responses to various therapies.
“It is not a one-size-fits-all solution,” she said. “Hence, relying only on an AI-enabled algorithm to diagnose complex disorders may not be a good idea.”
It’s also important to have layers of security in place, so that AI can be used in a responsible manner without compromising patient privacy, according to Bandyopadhyay.
“As generative AI gains popularity, we also need to think about ethical concerns and discuss who is responsible for the clinical contents or decisions,” she added.
Future of AI in sleep medicine
Sleep medicine is “well-positioned” to incorporate AI, Bandyopadhyay said, as it involves interpreting body signals and “complex psychosocial processes” that work in tandem with the environment.
“AI forms the perfect triad between clinicians and patients.”
“Untreated sleep disorders can lead to adverse cardiometabolic and neurocognitive outcomes, making the ability to monitor one’s sleep in a meaningful manner and utilize that clinical data to improve sleep a critical need for our field,” she said.
If used correctly, AI can also help to alleviate physician burnout and improve patients’ access to care, she said.
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“In the U.S., the estimated patient-to-physician ratio among sleep medicine doctors is 43,000 to 1,” Bandyopadhyay noted.
“There aren’t enough physicians, and that leads to poor access to care.”
“If I had a tool that could screen my patients for poor quality or quantity of sleep, summarize that data for me, help me document my conversations with the patient, and alert me if my patient is not using the therapy as prescribed, then I would certainly be able to direct all my time and effort into improving the care I provide to my patients.”
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While AI is a powerful tool, Bandyopadhyay said clinicians must make sure to use it for “the right patient and the right cause.”
“AI forms the perfect triad between clinicians and patients, bridging the gap and empowering patients and clinicians to optimize good sleep health.”
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