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Dementia prediction using novel IOTM (Internet of Things in Medical) architecture framework.

Authors :
Pavitra, B.
Singh, D. Narendar
Sharma, Sudhir Kumar
Hashmi, Mohammad Farukh
Source :
Intelligent Data Analysis. 2023 Supplement 1, Vol. 27, p29-45. 17p.
Publication Year :
2023

Abstract

In the last decades the health care developments highly rise the level of ages of world population. This improvement was accompanied by increasing the diseases related with elder like Dementia, which Alzheimer's disease represents the most common form. The present studies aim to design and implementation a medical system for improving the life of Alzheimer's disease persons and ease the burden of their caregivers. AI is transforming the practice of medicine. It's helping doctors diagnose patients more accurately, make predictions about patient's future health, and recommend better treatments. AI goes beyond the foundations of deep learning to give you insight into the nuances of applying AI to medical use cases. Diagnosis is about identifying disease. By building an algorithm we can diagnosis chest X-ray and determine whether it contains disease, another algorithm that will look at brain MRIs and identify the location of tumours in those brain MRIs health of the patients lab values and their demographics and use those to predict the risk of an event. A Smart IOT Interactive Assistance is a technological device that continuously monitors the stability of an Alzheimer's patient, indicates their position on a map, automatically reminds them to take their prescriptions, and has a call button for any emergencies they could experience during the day. The system has two components, one of which the patient wears and the other of which is an IoT platform application utilized by the caregiver. The motion processing unit sensor, GPS, heart rate sensor with microcontrollers, and LCD display were used to construct the wearable device. An Internet of Things (IoT) platform supports this device, allowing the caregiver to communicate with the patient from any location. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1088467X
Volume :
27
Database :
Academic Search Index
Journal :
Intelligent Data Analysis
Publication Type :
Academic Journal
Accession number :
173929479
Full Text :
https://doi.org/10.3233/IDA-237431