A selected subset of psychological and functional assessments to efficiently classify Alzheimer’s disease from healthy controls using novelty detection

Shuo Liu; Qinyong  Ye; Damien Coyle; Junxiu Liu; Yi Cao; Li Su; Xuemei Ding

A selected subset of psychological and functional assessments to efficiently classify Alzheimer’s disease from healthy controls using novelty detection

Shuo Liu
, Qinyong Ye
, Damien Coyle
, Junxiu Liu
, Yi Cao
, Li Su
, Xuemei Ding

Research output: Contribution to conference › Abstract › peer-review

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Abstract

Psychological/functional assessments (PFA) have been widely used in clinical practice for
Alzheimer’s disease (AD) diagnosis and prognosis due to their lower cost relative to blood test
and brain imaging. However, applying a number of sub-assessments is time-consuming, and
particularly impracticable for patients with cognitive impairment. This study aims to find a
subset of PFA for efficient AD diagnosis.

Original language	English
Publication status	Published (in print/issue) - 18 Mar 2020
Event	Alzheimer's Research UK - , United Kingdom Duration: 17 Mar 2020 → …

Conference

Conference	Alzheimer's Research UK
Abbreviated title	ARUK 2020
Country/Territory	United Kingdom
Period	17/03/20 → …

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

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A selected subset of psychological and functional assessments to efficiently classify Alzheimer’s disease from healthy controls using novelty detectionAuthor Accepted Manuscript, 74.3 KB

Efficient level set method for novelty detection
Liu, S. (Author), Ding, X. (Supervisor), Liu, J. (Supervisor) & Coyle, D. (Supervisor), Mar 2024
Student thesis: Doctoral Thesis

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title = "A selected subset of psychological and functional assessments to efficiently classify Alzheimer{\textquoteright}s disease from healthy controls using novelty detection",

abstract = "Psychological/functional assessments (PFA) have been widely used in clinical practice for Alzheimer{\textquoteright}s disease (AD) diagnosis and prognosis due to their lower cost relative to blood test and brain imaging. However, applying a number of sub-assessments is time-consuming, and particularly impracticable for patients with cognitive impairment. This study aims to find a subset of PFA for efficient AD diagnosis. ",

author = "Shuo Liu and Qinyong Ye and Damien Coyle and Junxiu Liu and Yi Cao and Li Su and Xuemei Ding",

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T1 - A selected subset of psychological and functional assessments to efficiently classify Alzheimer’s disease from healthy controls using novelty detection

AU - Liu, Shuo

AU - Ye, Qinyong

AU - Coyle, Damien

AU - Liu, Junxiu

AU - Cao, Yi

AU - Su, Li

AU - Ding, Xuemei

PY - 2020/3/18

Y1 - 2020/3/18

N2 - Psychological/functional assessments (PFA) have been widely used in clinical practice for Alzheimer’s disease (AD) diagnosis and prognosis due to their lower cost relative to blood test and brain imaging. However, applying a number of sub-assessments is time-consuming, and particularly impracticable for patients with cognitive impairment. This study aims to find a subset of PFA for efficient AD diagnosis.

AB - Psychological/functional assessments (PFA) have been widely used in clinical practice for Alzheimer’s disease (AD) diagnosis and prognosis due to their lower cost relative to blood test and brain imaging. However, applying a number of sub-assessments is time-consuming, and particularly impracticable for patients with cognitive impairment. This study aims to find a subset of PFA for efficient AD diagnosis.

M3 - Abstract

T2 - Alzheimer's Research UK

Y2 - 17 March 2020

ER -

A selected subset of psychological and functional assessments to efficiently classify Alzheimer’s disease from healthy controls using novelty detection

Abstract

Conference

UN SDGs

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Student theses

Efficient level set method for novelty detection

Cite this