Matches in SemOpenAlex for { <https://semopenalex.org/work/W3107825668> ?p ?o ?g. }
Showing items 1 to 73 of
73
with 100 items per page.
- W3107825668 endingPage "304" @default.
- W3107825668 startingPage "295" @default.
- W3107825668 abstract "Alzheimer’s disease (AD) has become a major health problem over the past few decades. AD can be defined as a neurodegenerative disorder that causes the brain cells to degenerate and die. AD is the most popular cause of dementia. AD is likely to be more observant in elderly people that are people above 65 years of age. Memory loss is one of the prominent symptoms of AD. The people suffering from AD tend to repeat questions or statements, or eventually may forget the names of their family members. Detection of AD has already been done using several machine learning techniques like supervised learning, unsupervised learning, and reinforcement learning as well as deep learning techniques. In this paper, we have tried to detect AD using Nearest Neighbor, K-Nearest Neighbor, and Weighted K-Nearest Neighbor algorithm. In the area of AD detection using machine learning techniques, KNN has already been applied but a detailed computational overview of different variants of the nearest neighbor algorithms has been performed in this paper which will add a new dimension in the medical domain. We have considered four classes for our work namely Normal, Very mild, Mild, and Moderate. We have evaluated the performance of our system using three performance metrics namely Precision, Recall, and F1 score." @default.
- W3107825668 created "2020-12-07" @default.
- W3107825668 creator A5005025905 @default.
- W3107825668 creator A5027433743 @default.
- W3107825668 creator A5036137506 @default.
- W3107825668 creator A5039664511 @default.
- W3107825668 date "2020-11-28" @default.
- W3107825668 modified "2023-09-25" @default.
- W3107825668 title "Performance Analysis of Nearest Neighbor, K-Nearest Neighbor and Weighted K-Nearest Neighbor for the Classification of Alzheimer Disease" @default.
- W3107825668 cites W1670213260 @default.
- W3107825668 cites W2510620627 @default.
- W3107825668 cites W2796349731 @default.
- W3107825668 cites W2805494981 @default.
- W3107825668 cites W2901966692 @default.
- W3107825668 cites W2936743816 @default.
- W3107825668 cites W2940561310 @default.
- W3107825668 doi "https://doi.org/10.1007/978-981-15-7394-1_28" @default.
- W3107825668 hasPublicationYear "2020" @default.
- W3107825668 type Work @default.
- W3107825668 sameAs 3107825668 @default.
- W3107825668 citedByCount "4" @default.
- W3107825668 countsByYear W31078256682021 @default.
- W3107825668 countsByYear W31078256682022 @default.
- W3107825668 crossrefType "book-chapter" @default.
- W3107825668 hasAuthorship W3107825668A5005025905 @default.
- W3107825668 hasAuthorship W3107825668A5027433743 @default.
- W3107825668 hasAuthorship W3107825668A5036137506 @default.
- W3107825668 hasAuthorship W3107825668A5039664511 @default.
- W3107825668 hasConcept C100660578 @default.
- W3107825668 hasConcept C113238511 @default.
- W3107825668 hasConcept C119857082 @default.
- W3107825668 hasConcept C142724271 @default.
- W3107825668 hasConcept C153180895 @default.
- W3107825668 hasConcept C154945302 @default.
- W3107825668 hasConcept C15744967 @default.
- W3107825668 hasConcept C180747234 @default.
- W3107825668 hasConcept C2779134260 @default.
- W3107825668 hasConcept C2779483572 @default.
- W3107825668 hasConcept C41008148 @default.
- W3107825668 hasConcept C71924100 @default.
- W3107825668 hasConcept C8038995 @default.
- W3107825668 hasConceptScore W3107825668C100660578 @default.
- W3107825668 hasConceptScore W3107825668C113238511 @default.
- W3107825668 hasConceptScore W3107825668C119857082 @default.
- W3107825668 hasConceptScore W3107825668C142724271 @default.
- W3107825668 hasConceptScore W3107825668C153180895 @default.
- W3107825668 hasConceptScore W3107825668C154945302 @default.
- W3107825668 hasConceptScore W3107825668C15744967 @default.
- W3107825668 hasConceptScore W3107825668C180747234 @default.
- W3107825668 hasConceptScore W3107825668C2779134260 @default.
- W3107825668 hasConceptScore W3107825668C2779483572 @default.
- W3107825668 hasConceptScore W3107825668C41008148 @default.
- W3107825668 hasConceptScore W3107825668C71924100 @default.
- W3107825668 hasConceptScore W3107825668C8038995 @default.
- W3107825668 hasLocation W31078256681 @default.
- W3107825668 hasOpenAccess W3107825668 @default.
- W3107825668 hasPrimaryLocation W31078256681 @default.
- W3107825668 hasRelatedWork W2146076056 @default.
- W3107825668 hasRelatedWork W2167440101 @default.
- W3107825668 hasRelatedWork W2782789473 @default.
- W3107825668 hasRelatedWork W3046775127 @default.
- W3107825668 hasRelatedWork W3087576162 @default.
- W3107825668 hasRelatedWork W3196155444 @default.
- W3107825668 hasRelatedWork W3209574120 @default.
- W3107825668 hasRelatedWork W3210156800 @default.
- W3107825668 hasRelatedWork W4285260836 @default.
- W3107825668 hasRelatedWork W4287665842 @default.
- W3107825668 isParatext "false" @default.
- W3107825668 isRetracted "false" @default.
- W3107825668 magId "3107825668" @default.
- W3107825668 workType "book-chapter" @default.