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PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
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TZID:Australia/Brisbane
BEGIN:STANDARD
DTSTART:19920301T020000
TZOFFSETFROM:+1100
TZOFFSETTO:+1000
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BEGIN:VEVENT
DTSTAMP:20260518T073441Z
UID:9C782BEA-0A65-4C84-9F66-B7131029290F
DTSTART;TZID=Australia/Brisbane:20260511T141500
DTEND;TZID=Australia/Brisbane:20260511T150000
DESCRIPTION:Abstract:\n\nBlood monitoring is essential for the early detect
 ion\, diagnosis\, and management of a wide range of health conditions. How
 ever\, conventional blood analysis often depends on invasive sampling\, la
 boratory infrastructure\, and intermittent testing\, which can limit acces
 sibility and continuous monitoring. These limitations motivate the explora
 tion of electromagnetic sensing as a promising alternative for blood analy
 sis.\n\nThis talk presents the broader vision of monitoring blood using el
 ectromagnetic sensing technologies\, with emphasis on how the dielectric a
 nd dispersive properties of blood change with its composition and physiolo
 gical state. Variations in parameters such as hematocrit\, hemoglobin\, an
 d temperature can influence the electromagnetic response of blood across f
 requency. By studying these signatures\, new pathways can be explored towa
 rd non-invasive blood assessment.\n\nThe presentation will discuss how art
 ificial intelligence can support this journey by learning complex relation
 ships between electromagnetic measurements and blood-related parameters\, 
 improving feature extraction\, identifying informative frequency regions\,
  and enabling robust prediction and classification. At the same time\, the
  talk will highlight major challenges in this field\, including biological
  variability\, measurement sensitivity\, calibration\, generalization acro
 ss subjects and devices\, interpretability of AI models\, and the constrai
 nts imposed by real-world sensor and hardware design.\n\nSpeaker(s): Dr. H
 ajar Abedi \, \n\nRoom: 914\, Bldg: 46 (Andrew N. Liveris Building)\, The 
 University of Queensland\, Brisbane\, Queensland\, Australia
LOCATION:Room: 914\, Bldg: 46 (Andrew N. Liveris Building)\, The University
  of Queensland\, Brisbane\, Queensland\, Australia
ORGANIZER:h.espinosa@griffith.edu.au
SEQUENCE:16
SUMMARY:AI-Enabled Electromagnetic Sensing for Blood Analysis: Challenges\,
  Opportunities\, and Clinical Potential
URL;VALUE=URI:https://events.vtools.ieee.org/m/558620
X-ALT-DESC:Description: <br /><p><span style="font-size: 12pt\; line-height
 : 115%\; font-family: helvetica\, arial\, sans-serif\;"><img style="float:
  right\;" src="https://events.vtools.ieee.org/vtools_ui/media/display/5fb0
 4e26-1de5-42d2-9e56-97d5800d1d08" width="229" height="344"></span></p>\n<p
 ><span style="font-size: 14pt\;"><strong><span style="line-height: 115%\; 
 font-family: helvetica\, arial\, sans-serif\;">Abstract:</span></strong></
 span></p>\n<p><span style="font-size: 12pt\; line-height: 115%\; font-fami
 ly: helvetica\, arial\, sans-serif\;">Blood monitoring is essential for th
 e early detection\, diagnosis\, and management of a wide range of health c
 onditions. However\, conventional blood analysis often depends on invasive
  sampling\, laboratory infrastructure\, and intermittent testing\, which c
 an limit accessibility and continuous monitoring. These limitations motiva
 te the exploration of electromagnetic sensing as a promising alternative f
 or blood analysis.</span></p>\n<p><span style="font-size: 12pt\; line-heig
 ht: 115%\; font-family: helvetica\, arial\, sans-serif\;">This talk presen
 ts the broader vision of monitoring blood using electromagnetic sensing te
 chnologies\, with emphasis on how the dielectric and dispersive properties
  of blood change with its composition and physiological state. Variations 
 in parameters such as hematocrit\, hemoglobin\, and temperature can influe
 nce the electromagnetic response of blood across frequency. By studying th
 ese signatures\, new pathways can be explored toward non-invasive blood as
 sessment.</span></p>\n<p><span style="font-size: 12pt\; line-height: 115%\
 ; font-family: helvetica\, arial\, sans-serif\;">The presentation will dis
 cuss how artificial intelligence can support this journey by learning comp
 lex relationships between electromagnetic measurements and blood-related p
 arameters\, improving feature extraction\, identifying informative frequen
 cy regions\, and enabling robust prediction and classification. At the sam
 e time\, the talk will highlight major challenges in this field\, includin
 g biological variability\, measurement sensitivity\, calibration\, general
 ization across subjects and devices\, interpretability of AI models\, and 
 the constraints imposed by real-world sensor and hardware design.</span></
 p>
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