Artificial intelligence can improve efficiencies in sleep disorder treatment, resulting in more patient-centered care and better outcomes.
FREMONT, CA: Researchers today are using Artificial Intelligence (AI) to boost efficiencies and precision in sleep disorder treatment, leading to improved care. Sleep disorder treatment centers collect massive amounts of data, enabling AI and machine learning algorithms to advance sleep care. These technologies have the potential to create more accurate diagnoses, prediction of disease and treatment plan, classification of disease types, precision in scoring, and sleep treatment optimization and personalization. Know more here.
Researchers are also using AI to automate sleep scoring while identifying new insights from sleep data. Additionally, AI might help clinicians understand mechanisms underlying obstructive sleep apnea, so they can select the right treatment for the right patient at the right time, as opposed to one-size-fits-all or trial and error methods. The AI potential for clinical impact includes broadening the reach of clinical sleep medicine, augmenting clinical decision-making, and improving the accuracy and reliability of at-home treatment systems.
Due to the vast amounts of data collected by sleep centers, AI and machine learning could advance sleep care, resulting in more accurate diagnoses, prediction of disease and treatment prognosis, characterization of disease, precision in sleep scoring, and optimization and personalization sleep treatments. AI could be used to automate sleep scoring while identifying additional insights from sleep data. AI might help clinicians understand the mechanisms underlying sleep apnea.
Significant considerations for integrating AI into sleep medicine practice include transparency and disclosure, testing on data, and laboratory integration. It is recommended that manufacturers disclose the intended population and aim of any program used in evaluating patients, intended for clinical use on independent data, and help sleep disorder treatment in the evaluation of AI-based software performance. AI tools hold significant promise for medicine, but there have also been many hypes, exaggerated claims. Healthcare facilities want to interface with industry in a way that will foster the safe and productive use of AI to benefit patients. These tools can only benefit patients if used with proper oversight.