Medication adherence monitoring with tracking automation and emergency assistance

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dc.contributor.author Jamkhandikar, Irfan
dc.contributor.author Shaikh, Shadab Ali Murad Ali (17DCO74)
dc.contributor.author Kazi, Obaid Abdul Aziz (17DCO69)
dc.contributor.author Ansari, Mohd Adnan Azimuddin (17DCO63)
dc.contributor.author Shaikh, Romaan Usman (16DCO77)
dc.date.accessioned 2021-11-03T07:22:31Z
dc.date.available 2021-11-03T07:22:31Z
dc.date.issued 2020-05
dc.identifier.uri http://localhost:8080/xmlui/handle/123456789/3617
dc.description.abstract In today‘s busy world, people are not able to track/monitor the medication events of their dear ones who are suffering from diseases appropriately. There are times when a patient “forgets” to have or “doesn‘t take” the prescribed medicine at a given schedule. Such scenarios in medical term is known as Medication Non-adherence (MNA). The MNA to prescribed treatment is thought to cause at least 100,000 preventable deaths and $100 billion in preventable medical costs per year. The reason for Nonadherence shows 63% for forgetfulness.[5] A study kempegowda institute of medical sciences & research center, Bangalore, India depicts over 21% of MNA problem in hypertensive patients.[9] The technology that could help in improving the MNA related problem is over 28% combining phone call (10%), live chat (3%), SMS (9%), Mobile applications (5-8%).[11] Despite, The medical profession largely ignores MNA or sees it as a patient problem and not a physician or health system problem.[5] This is a great loss to society considering the health effects and causes being generated from this issue. This report highlights various mechanisms that can be thought to integrate in order to improve the adherence of a patient.[1] Unlike already existing applications, Our Application (MAMTE) will guide a patient through automated calls, maintenance & tracking of log of events, & will use state of the art technologies such as Google Cloud Vision A.I and Deep learning neural networks for text and handwriting detection-recognition and extracting medication events through images. Keywords: Medication Non-Adherence, handwriting recognition, google cloud vision A.I, deep learning neural networks, medication events tracker. en_US
dc.language.iso en en_US
dc.publisher AIKTC en_US
dc.subject Project Report - CO en_US
dc.title Medication adherence monitoring with tracking automation and emergency assistance en_US
dc.type Other en_US


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