BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/Phoenix BEGIN:STANDARD DTSTART:19671029T010000 TZOFFSETFROM:-0600 TZOFFSETTO:-0700 TZNAME:MST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260404T202337Z UID:8DB028BD-43B4-46DF-BAB7-47BA47F696DB DTSTART;TZID=America/Phoenix:20260325T110000 DTEND;TZID=America/Phoenix:20260325T120000 DESCRIPTION:The majority of the health care costs related to the treatment of chronic and infectious diseases are attributed to direct care costs (e. g.\, hospital admissions and readmissions). The prevalence of chronic dise ases and associated costs in the United States is growing at an alarming p ace. The COVID-19 pandemic has further impacted the health of high-risk in dividuals by increasing the likelihood of more severe illness for those wi th underlying health conditions and associated healthcare costs. There hav e been ample efforts from researchers and clinicians to develop remote hea lthcare systems and wearable devices to manage patients with chronic and i nfectious diseases in home settings\, which has reduced the burden on inpa tient care facilities and gained further momentum during the COVID-19 pand emic. Yet\, there is a lack of reliable wearable devices that can provide clinically acceptable information to healthcare professionals\, as well as a lack of emphasis on validating wearable and artificial intelligence tec hnologies in representative populations to enable a reliable and equitable remote health management system. This talk will present the challenges an d potential solutions for developing tools (i.e.\, wearable sensors and co mputational algorithms) for reliable and equitable remote patient monitori ng systems for chronic and infectious diseases.\n\nSpeaker(s): Md Mobashir Hasan Shandhi\n\nVirtual: https://events.vtools.ieee.org/m/540506 LOCATION:Virtual: https://events.vtools.ieee.org/m/540506 ORGANIZER:embs.phx@ieee.org SEQUENCE:22 SUMMARY:Wearable Sensors and Artificial Intelligence Algorithms for Monitor ing Chronic and Infectious Diseases URL;VALUE=URI:https://events.vtools.ieee.org/m/540506 X-ALT-DESC:Description: <br /><p class="MsoNormal" style="margin-bottom: 6. 0pt\;"><span style="font-family: 'Arial'\,sans-serif\;">The majority of th e health care costs related to the treatment of chronic and infectious dis eases are attributed to direct care costs (e.g.\, hospital admissions and readmissions). The prevalence of chronic diseases and associated costs in the United States is growing at an alarming pace. The COVID-19 pandemic ha s further impacted the health of high-risk individuals by increasing the l ikelihood of more severe illness for those with underlying health conditio ns and associated healthcare costs. There have been ample efforts from res earchers and clinicians to develop remote healthcare systems and wearable devices to manage patients with chronic and infectious diseases in home se ttings\, which has reduced the burden on inpatient care facilities and gai ned further momentum during the COVID-19 pandemic. Yet\, there is a lack o f reliable wearable devices that can provide clinically acceptable informa tion to healthcare professionals\, as well as a lack of emphasis on valida ting wearable and artificial intelligence technologies in representative p opulations to enable a reliable and equitable remote health management sys tem. This talk will present the challenges and potential solutions for dev eloping tools (i.e.\, wearable sensors and computational algorithms) for r eliable and equitable remote patient monitoring systems for chronic and in fectious diseases.</span></p> END:VEVENT END:VCALENDAR