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Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/807
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dc.contributor.authorS, Hemkiran-
dc.contributor.authorSadasivam, Sudha-
dc.date.accessioned2024-08-24T05:56:26Z-
dc.date.available2024-08-24T05:56:26Z-
dc.date.issued2023-
dc.identifier.other17254691213-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/807-
dc.description.abstractAlzheimer’s disease (AD) is a neurodegenerative disorder, and is a leading cause of dementia cases in the world today. It is estimated that in excess of 100 million people will be affected by this dreadful disease by 2050 (Sadigh-Eteghad et al. 2015). AD adversely affects the functioning of the brain leading to impediments such as loss of memory, depression, swings in behavior, arduousness in performing daily activities, etc. Detecting AD at an early stage can retard the adverse effects that may manifest later in patients (Khan & Zubair 2019). Several studies attribute the occurrence of AD to two hypotheses. The first, amyloid hypothesis propounds that the incidence of AD is due to the build-up of β-amyloid (Aβ) proteins in the form of plaques that accumulate in the neurons of the human brain. The second, cholinergic hypothesis proposes that the dysfunction of acetylcholine which transmits information between neurons, causes rapid degeneration of cognitive abilities, leading to AD. Although several therapies have mitigated the symptoms, no clinical methods have been identified thus far, to effectively treat AD (Long & Holtzman 2019). Therefore, identifying specific drugs to cure AD is paramount.en_US
dc.language.isoenen_US
dc.publisherAnna Universityen_US
dc.subjectDrug bioactivityen_US
dc.subjectAlzemiersen_US
dc.subjectMachine learningen_US
dc.titleDrug Bioactivity Prediction for Alzheimeren_US
dc.typeThesisen_US
Appears in Collections:Computer Science & Engineering

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