Title : Navigating intelligent healthcare systems for better respiratory care
Abstract:
Intelligence has been an integral component of every aspect in all most all arenas of life. In the healthcare industry, the degree to which it has been impacted is comparatively low and the progress is in smaller steps when compared to those made in other fields. This can be attributed to several challenges and hurdles faced in healthcare systems. Adding to this, intelligence is not justified in beyond proof-of-concept studies. Recent years however have embraced hybrid models that involve incorporation of intelligence from AI systems, besides leaving the ultimate responsibility of disease identification/outcomes in the hands of the clinician as a means of critical intervention. Intelligent healthcare systems combine artificial intelligence (AI), machine learning (ML), Internet of Medical Things (IoMT), big data analytics, and telemedicine to improve diagnosis, monitoring, and treatment of respiratory diseases. Respiratory medicine benefits greatly because many lung diseases require continuous monitoring, early detection, and rapid intervention. AI analyses lung scans and spirometry data for early detection of respiratory issues, often outperforming traditional methods. Smart inhalers track usage, technique, and adherence via sensors, sending data to providers for timely adjustments. Remote monitoring tools, including wearables and telemedicine platforms, enable continuous tracking of oxygen levels and symptoms, reducing hospital visits. Growing number of studies have indicated the successful implications of intelligence through analytics in areas including patient stratification, decisions at triage and prediction of severity levels of disease.
