Computer-aided diagnosis and prediction in brain disorders
- URL: http://arxiv.org/abs/2206.14683v1
- Date: Wed, 29 Jun 2022 14:39:08 GMT
- Title: Computer-aided diagnosis and prediction in brain disorders
- Authors: Vikram Venkatraghavan, Sebastian R. van der Voort, Daniel Bos, Marion
Smits, Frederik Barkhof, Wiro J. Niessen, Stefan Klein, Esther E. Bron
- Abstract summary: Computer-aided methods have shown added value for diagnosing and predicting brain disorders.
This chapter will provide insight into the type of methods, their working, their input data and the types of output they provide.
- Score: 4.1952343579390226
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Computer-aided methods have shown added value for diagnosing and predicting
brain disorders and can thus support decision making in clinical care and
treatment planning. This chapter will provide insight into the type of methods,
their working, their input data - such as cognitive tests, imaging and genetic
data - and the types of output they provide. We will focus on specific use
cases for diagnosis, i.e. estimating the current 'condition' of the patient,
such as early detection and diagnosis of dementia, differential diagnosis of
brain tumours, and decision making in stroke. Regarding prediction, i.e.
estimation of the future 'condition' of the patient, we will zoom in on use
cases such as predicting the disease course in multiple sclerosis and
predicting patient outcomes after treatment in brain cancer. Furthermore, based
on these use cases, we will assess the current state-of-the-art methodology and
highlight current efforts on benchmarking of these methods and the importance
of open science therein. Finally, we assess the current clinical impact of
computer-aided methods and discuss the required next steps to increase clinical
impact.
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