Big data and artificial intelligence are rapidly transforming the healthcare and medical landscape, ushering in the era of ‘precision medicine’. This new approach to medical research focuses on utilizing data-driven insights to tailor treatments and interventions to patient’s needs. Insomnia research is one particular area where the influx of data and the application of artificial intelligence has yielded significant advancements. The use of big data has enabled researchers to significantly improve the accuracy and speed of clinical trials, as well as develop predictive models that generate more effective recovery treatments.
Big data in insomnia research is mainly gathered from electronic health records (EHR) and patient feedback. By leveraging data from large scale clinical trials and aggregating sources of evidence-based practice, systematic reviews and cohorts, researchers can find meaningful relationships in the data. With this data, they are able to discover correlations between individuals. Insights from this population-level information allow researchers to build and evaluate hotel intervention strategies or real-world evidence to identify causes of insomnia and interactions that lead to the most successful treatment outcomes.
In addition to EHRs, AI-driven technologies are being used to monitor sleep with wearable devices and apps. These tools are more accurate than conventional sleep tests and can track sleep quality, as well as examine associated behaviors. With continuous, real-time monitoring of sleep, AI-driven technologies can provide a range of new enablers for exploring diagnostic insights into insomnia for research and clinical use. AI-based methods can also be used to generate predictive models to forecast the evolution of a given case and will ultimately lead to more personalized sleep therapies and treatments.
Data science and AI also provide a powerful aid in identifying patients in certain trials. Stratifying population groups allows researchers to select sample sizes more precisely and accurately based on given criteria. This approach is particularly helpful in understanding, predicting, and managing on-trial performance, ultimately leading to faster and more accurate results. Rather than relying solely on demographics such as age, gender or medical history, personalized therapy and tailored studies can be conducted with more granular and precise data obtained through modern technologies like AI and machine learning.
Modern data science is revolutionizing insomnia research and impacting clinical trial processes. Big data and AI-driven technologies allow clinical trial researchers to discover correlations between individual patients, generate detailed models to predict patient behavior, and accurately pinpoint potential participants for trials based on various criteria. Through targeted sleep interventions and treatments, participating patients at MCR will have the benefit of an interactive question-and-answer session or a questionnaire-based assessment to receive personalized insights into restful sleep.
As the use of big data and AI grow in prominence, insomnia researchers can continue to use advances in technology to make remarkable breakthroughs in the understanding and treatment this commonly occurring disorder. By taking advantage of population-level information to develop more effective intervention strategies, personalized sleep therapies can be developed that lead to more successful treatment outcomes for individuals dealing with insomnia.
At Miami Clinical Research, we are dedicated to bringing the latest pharmaceutical studies to life with the help of our state-of-the-art equipment and technology. Our cutting-edge facilities and reliable services provide Sponsors with the confidence and assurance that their research studies are being conducted at a “Top 10 Clinical Research Provider.” To learn more, call 305-433-6496 or email us at firstname.lastname@example.org.