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Artificial Intelligence in Dementia Research

Alzheimer's Research & Therapy presents a thematic series focusing on the use of artificial intelligence in dementia research.

Guest Editors: James Cole1, Kerstin Ritter2 & Bin Zhang3
1 University College London; 2 Charité - Universitätsmedizin Berlin; 3 Icahn School of Medicine at Mount Sinai

Submission Deadline: 15 February 2021

Artificial Intelligence in Dementia

The aim of this series is to showcase cutting edge research using Artificial Intelligence (AI), machine (deep) learning and related techniques to study dementia.

Often inspired by models of human neural networks, AI has recently transformed the fields of computer vision, image analysis, natural language processing, automation and robotics. By harnessing recent developments in computing infrastructure and processing power, AI has set new state-of-the-art benchmarks for performance, generated new innovations in engineering and steadily become part of the mainstream of science and technology.

Amidst the hype, there is genuine excitement about the power of AI to benefit healthcare across the board, and dementia is no exception. Already AI and machine learning have improved neuroimage analysis, led to discoveries of new biological pathways and systems implicated in dementia and related diseases.

However, many critical research questions remain open, for example:

  • How to discover intrinsic patterns and mechanisms underlying massive, highly heterogeneous biological data? 
  • How to best integrate data from different modalities or different cohort studies? 
  • How to accelerate development of novel therapeutics for dementia by leveraging all existing knowledge and data? 
  • How to interpret results from deep learning? 
  • How to embed ethical considerations in intelligent machine decisions?

Answering such questions will be fundamental in the success of AI for dementia, and we hope to attract research that contributes towards this goal.

The series is organised into three broad thematic categories, Basic Mechanisms, Translational Research and Clinical Applications. We invite original research submissions from scientists using AI, machine learning or related advanced statistical methods to analyse dementia related data across all levels of biology including molecular, cellular, organismal, behavioural and population levels. 

This covers research at any scale; from microscopic, through mesoscopic to macroscopic and beyond to population level epidemiology. These can include but not limit to genetics, 'omics, cell imaging, brain imaging, cognitive assessments, smart home, wearable monitoring devices, target identification, drug discovery, and clinical decision-making for dementia and related diseases. 

For this series Alzheimer's Research & Therapy (Impact Factor: 6.116) will publish both commissioned and non-commissioned content. All submissions will be undergo peer review. Submissions of both original research and reviews will be considered, and accepted manuscripts will be published on a timely, ongoing basis.

The submission deadline for this series has now passed. Articles will continue to publish as part of this series as they are available throughout 2021.

  1. Generative adversarial networks (GAN) can produce images of improved quality but their ability to augment image-based classification is not fully explored. We evaluated if a modified GAN can learn from magneti...

    Authors: Xiao Zhou, Shangran Qiu, Prajakta S. Joshi, Chonghua Xue, Ronald J. Killiany, Asim Z. Mian, Sang P. Chin, Rhoda Au and Vijaya B. Kolachalama

    Citation: Alzheimer's Research & Therapy 2021 13:60

    Content type: Research

    Published on:

  2. Recent DNA/RNA sequencing and other multi-omics technologies have advanced the understanding of the biology and pathophysiology of AD, yet there is still a lack of disease-modifying treatments for AD. A new ap...

    Authors: Yadi Zhou, Jiansong Fang, Lynn M. Bekris, Young Heon Kim, Andrew A. Pieper, James B. Leverenz, Jeffrey Cummings and Feixiong Cheng

    Citation: Alzheimer's Research & Therapy 2021 13:24

    Content type: Research

    Published on:

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