Sleep Disorders diagnosis and treatment augmented by Artificial Intelligence

Highlights

  • Artificial Intelligence find ways to cure sleep disorders
  • Insightful knowledge about AI technology in the medical industry

 

Artificial Intelligence is a new breather for the medical industry. As it helps in curing several medical illnesses, presenting the world with new possibilities. The Journal of Clinical Sleep Medicine has accepted the paper from the American Academy of Sleep Medicine. It states that during polysomnography- the electrophysiological data collected, qualifies for advanced analysis with AI and Machine learning.

 

AI in Sleep Medicine

Dr. Cathy Goldstein, associate professor of Sleep Medicine and Neurology at the University of Michigan said that when they think AI in sleep medicine the most emphasis is given on scoring of sleep and related events. The process of sleep laboratories and sleep technologist time for direct patient care will be aligned.

As the data collected is enormous by the sleep centers, the diagnosis elevates the accuracy level and with the help of AI and Machine learning advancement in sleep-care is possible along with the treatment prognosis, characterization of disease subtypes, precision in sleep scoring, optimization and personalization of sleep treatments. Furthermore, AI can automate sleep scoring and read more sleep data.

The current summary metrics like the apnea-hypopnea index do not give predictions about health and quality life which are prima facie requirements of patients which can be achieved with the help of AI. AI explains obstructive sleep apnea mechanisms clearly, that makes the correct diagnosis of the right patient at the right time with the right treatment. The implementation of AI into sleep medicine has three things to look out for like transparency and disclosure, testing of novel data and laboratory integration.

The revelation of population data and the intention of every program to check patients, test programs for clinical use, and aid sleep centers required to assess the performance of AI-based software. It should be noted that careful oversight of these tools, only will benefit the patient.

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