2021
DOI: 10.1186/s12859-021-04077-9
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Eye-color and Type-2 diabetes phenotype prediction from genotype data using deep learning methods

Abstract: Background Genotype–phenotype predictions are of great importance in genetics. These predictions can help to find genetic mutations causing variations in human beings. There are many approaches for finding the association which can be broadly categorized into two classes, statistical techniques, and machine learning. Statistical techniques are good for finding the actual SNPs causing variation where Machine Learning techniques are good where we just want to classify the people into different ca… Show more

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Cited by 12 publications
(11 citation statements)
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“…The random forest (RF) algorithm is an emerging and high precision machine learning algorithm that has been widely used in numerous fields, and of course, its role in the medical field is also exact. RF algorithms have been used for clinical diseases, such as using random forests to identify biomarkers for glioblastoma to find potential targets for treatment ( Li et al, 2021 ), building COPD risk prediction models ( Perret et al, 2021 ), and detecting and predicting type 2 diabetes ( Muneeb and Henschel, 2021 ), all with good results. An artificial neural network is a new type of algorithm derived from imitating the structure and function of the human brain, which has the characteristics of self-learning ability and high efficiency compared with the traditional machine learning algorithm.…”
Section: Discussionmentioning
confidence: 99%
“…The random forest (RF) algorithm is an emerging and high precision machine learning algorithm that has been widely used in numerous fields, and of course, its role in the medical field is also exact. RF algorithms have been used for clinical diseases, such as using random forests to identify biomarkers for glioblastoma to find potential targets for treatment ( Li et al, 2021 ), building COPD risk prediction models ( Perret et al, 2021 ), and detecting and predicting type 2 diabetes ( Muneeb and Henschel, 2021 ), all with good results. An artificial neural network is a new type of algorithm derived from imitating the structure and function of the human brain, which has the characteristics of self-learning ability and high efficiency compared with the traditional machine learning algorithm.…”
Section: Discussionmentioning
confidence: 99%
“…Following the publication of the original article [ 1 ], errors were identified in the affiliation and funding note.…”
Section: Correction To: Bmc Bioinformatics (2021) 22:198 Https://doiorg/101186/s12859-021-04077-9mentioning
confidence: 99%
“…PRS is a more substantial quantity than classification in machine learning because PRS predicts a particular person's tendency to have a specific disease or trait [6,7]. In contrast, machine learning classifies people into traits or categories [8].…”
Section: Introductionmentioning
confidence: 99%
“…In this article [8], researchers benchmarked 9 deep/machine learning algorithms for eye-color and type-2 diabetes prediction. In this article [12], researchers benchmarked PRS calculation using 4 tools: PRScise, Plink, LDpred-2, and Lassosum, which we also followed when comparing the machine learning with PRS.…”
Section: Introductionmentioning
confidence: 99%