Bayesian Network as a Decision Tool for Predicting ALS Disease
Clinical diagnosis of amyotrophic lateral sclerosis (ALS) is difficult in the early period. But blood tests are less time consuming and low cost methods compared to other methods for the diagnosis. The ALS researchers have been used machine learning methods to predict the genetic architecture of dis...
Main Authors: | Hasan Aykut Karaboga, Aslihan Gunel, Senay Vural Korkut, Ibrahim Demir, Resit Celik |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-01-01
|
Series: | Brain Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3425/11/2/150 |
Similar Items
-
Generation and characterization of transgenic mice expressing mitochondrial targeted red fluorescent protein selectively in neurons: modeling mitochondriopathy in excitotoxicity and amyotrophic lateral sclerosis
by: Wang Yi, et al.
Published: (2011-11-01) -
Decision-making and referral processes for patients with motor neurone disease: a qualitative study of GP experiences and evaluation of a new decision-support tool
by: Susan Baxter, et al.
Published: (2017-05-01) -
Far beyond the motor neuron: the role of glial cells in amyotrophic lateral sclerosis
by: Paulo Victor Sgobbi de Souza, et al. -
MRI data confirm the selective involvement of thalamic and amygdalar nuclei in amyotrophic lateral sclerosis and primary lateral sclerosis
by: Rangariroyashe H. Chipika, et al.
Published: (2020-10-01) -
Demographic characteristics of patients with motor neuron disease subject to conditions of large industrial city in West Siberia
by: A. V. Lebedev
Published: (2009-06-01)