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Early Detection in Alzheimer's Disease - 1st Edition - ISBN: 9780128222409

Early Detection in Alzheimer's Disease

1st Edition

Biological and Technological Advances

Editor: Dennis Chan
Paperback ISBN: 9780128222409
Imprint: Academic Press
Published Date: 1st December 2021
Page Count: 300
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Early Detection of Alzheimer’s Disease aims to introduce to a wide audience the high global priority problem of detecting AD prior to dementia onset. According to the Alzheimer’s Association, 5.8 million Americans are living with Alzheimer’s and care costs will cost the nation approximately $290 billion (2019 Alzheimer’s Disease Facts and Figures). With the failure of recent AD drug trials, many hypothesize that by the time symptoms appear, it is too late to be treated. Early detection can offer benefits such as more choice of medications, ability to participate in clinical trials, more time for family and for care planning. This book outlines potential solutions to the above problem using opportunities arising from the technology revolution, advances in neuroscience, and molecular biology. Most importantly, it discusses a paradigm shift from a reactive to a proactive diagnostic approach, aiming to detect disease before occurrence of symptoms. Topics covered include the use of sensing technologies (eg smartphones, smartwatches, Internet of Things) to detect early disease-related changes , the application of data science (machine learning/AI) to extract otherwise invisible disease features from these datasets and the potential to personalize diagnosis based on tracking changes in individual behaviours. Advances in blood-based biomarkers, brain imaging, and the potential for early diagnosis to aid interventions (lifestyle, dietary, pharmacological) to delay future development of dementia are also discussed.

Key Features

  • Outlines the importance of early diagnosis of Alzheimer’s Disease
  • Helps readers understand the limitations of current clinical approaches and the need for a paradigmatic shift in diagnostic practice
  • Discusses the potential role of technology in clinical practice using machine learning and artificial intelligence and the potential to personize diagnosis and treatment


Neuroscientists, neurologists, psychiatrists and nurse practitioners focused on AD

Table of Contents

1. Foreword

2. Introduction
Opportunities and challenges provided by the tech revolution
The need for futureproofing and the importance of mitigating against the risk of obsolescence

3. Early Alzheimer’s disease
The syndrome of mild cognitive impairment

4. The need for early diagnosis
Clinical, societal and health economic drivers
The aging population
Global inequalities in access to diagnostics
Scientific drivers
The need to integrate with basic neuroscience
Need for functionally relevant outcome measures

5. An overview of current diagnostic strategies
Cognitive testing
Clinical evaluation

6. Novel approaches to diagnosis
Opportunities arising from the tech revolution
App-based testing
Machine learning/AI
Big data
Personalised diagnostics
Advances in imaging
Advances in biomarkers, incl blood-based methods
Advances in cognitive testing

7. Challenges for the new approach
Ethical issues about early diagnosis in the absence of a cure

8. An eye to the future
Beyond diagnosis: how to use such approaches for intervention
Clinical trials
the emerging landscape of disease-modifying drugs
novel trial outcome measures
Non-pharmacological interventions
Next generation approaches


No. of pages:
© Academic Press 2021
1st December 2021
Academic Press
Paperback ISBN:

About the Editor

Dennis Chan

Dr. Chan, PhD MD FRCP is an academic neurologist with a special interest in the diagnosis of Alzheimer’s disease prior to the onset of dementia. He holds dual research doctorates in basic and clinical neuroscience. His NHS practice is based at Addenbrooke’s Hospital, Cambridge, where he undertakes clinics in general neurology, dementia and mild cognitive impairment. His research focuses on identifying alterations in the function of the entorhinal cortex (EC) and hippocampus in early Alzheimer's disease (AD), with the ultimate aim of diagnosing AD prior to symptom onset.

Affiliations and Expertise

Consultant Neurologist, Cambridge and Peterborough NHS Foundation Trust Hononary Associate Professor, University College London, London, UK

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