Early Diagnosis of Mild Cognitive Impairment with 2-Dimensional Convolutional Neural Network Classification of Magnetic Resonance Images

Research output: Contribution to conferencePaperScientificpeer-review

Abstract

We motivate and implement an Artificial Intelligence (AI) Computer Aided Diagnosis (CAD) framework, to assist clinicians in the early diagnosis of Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD). Our framework is based on a Convolutional Neural Network (CNN) trained and tested on functional Magnetic Resonance Images datasets. We contribute to the literature on AI-CAD frameworks for AD by using a 2D CNN for early diagnosis of MCI. Contrary to current efforts, we do not attempt to provide an AI-CAD framework that will replace clinicians, but one that can work in synergy with them. Our framework is cheaper and faster as it relies on small datasets without the need of high-performance computing infrastructures. Our work contributes to the literature on digital transformation of healthcare, health Information Systems, and NeuroIS, while it opens novel avenues for further research on the topic.
Original languageEnglish
Publication statusAccepted/In press - 2021
EventHawaii International Conference on System Sciences - Hawaii, United States
Duration: 5 Jan 20218 Jan 2021
Conference number: 54
http://hicss.hawaii.edu

Conference

ConferenceHawaii International Conference on System Sciences
Abbreviated titleHICSS
CountryUnited States
CityHawaii
Period5/01/218/01/21
Internet address

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