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DTSTART:20190109T140000Z
DTEND:20190109T150000Z
SUMMARY:Guest talk by Marcia Cescon: Decision Support Systems for Insulin Therapy in Type 1 Diabetes
DESCRIPTION:Marcia Cescon, Harvard University,<a rel="noopener noreferrer" href="https://scholar.google.com/citations?user=mDGQqlAAAAAJ&amp;hl=en" target="_blank"> google scholar profile</a><br />\n<br />\nDiabetes describes a group of metabolic diseases characterized by high blood glucose levels (hyperglycemia), caused by lack of insulin secretion by the pancreas, insulin action or both. The chronic diabetes hyperglycemia has multiple effects throughout the body associated with damage, dysfunction and failure of various organs. Diabetes affects as many as 33.5 million individuals in the United States with associated annual medical cost of $345 billion, and its incidence is increasing at an alarming rate.<br />\n<br />\nCurrent insulin therapies entail great effort, require frequent user intervention (insulin administration and blood glucose measurements) and a high degree of expertise from patients, caregivers and health care providers. Nevertheless, evidence shows failure to reach the desired glycemic targets for the majority of the population with diabetes.<br />\n<br />\nAlthough type 1 diabetes is currently incurable, automated insulin delivery systems can considerably improve glycemic outcomes and the quality of life of insulin treated subjects, leading to fewer complications and lower health care costs.<br />\n<br />\nIn this talk, I will present my contributions toward the development of decision support systems for insulin therapy in type 1 diabetes. In particular I will introduce an advisory system for once-a-day dosing of long-acting insulin analogs in multiple-daily-injection therapy, an insulin infusion set failure detection system and some recent ideas on how to deal with disturbances other than meals.<br />\n<br />\nAll are welcome!
X-ALT-DESC;FMTTYPE=text/html:Marcia Cescon, Harvard University,<a rel="noopener noreferrer" href="https://scholar.google.com/citations?user=mDGQqlAAAAAJ&amp;hl=en" target="_blank"> google scholar profile</a><br />\n<br />\nDiabetes describes a group of metabolic diseases characterized by high blood glucose levels (hyperglycemia), caused by lack of insulin secretion by the pancreas, insulin action or both. The chronic diabetes hyperglycemia has multiple effects throughout the body associated with damage, dysfunction and failure of various organs. Diabetes affects as many as 33.5 million individuals in the United States with associated annual medical cost of $345 billion, and its incidence is increasing at an alarming rate.<br />\n<br />\nCurrent insulin therapies entail great effort, require frequent user intervention (insulin administration and blood glucose measurements) and a high degree of expertise from patients, caregivers and health care providers. Nevertheless, evidence shows failure to reach the desired glycemic targets for the majority of the population with diabetes.<br />\n<br />\nAlthough type 1 diabetes is currently incurable, automated insulin delivery systems can considerably improve glycemic outcomes and the quality of life of insulin treated subjects, leading to fewer complications and lower health care costs.<br />\n<br />\nIn this talk, I will present my contributions toward the development of decision support systems for insulin therapy in type 1 diabetes. In particular I will introduce an advisory system for once-a-day dosing of long-acting insulin analogs in multiple-daily-injection therapy, an insulin infusion set failure detection system and some recent ideas on how to deal with disturbances other than meals.<br />\n<br />\nAll are welcome!

URL:https://www.cachet.dk/da/Calendar/2019/01/Mercia-Cescon
DTSTAMP:20260910T143100Z
UID:{AE235CDD-FF43-48AB-9BDF-90AB597A35E5}-20190109T140000Z-20190109T140000Z
LOCATION: Technical University of Denmark, , Building 324 Auditorium 030
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