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Optimized hybrid learning for multi disease prediction enabled by lion with butterfly optimization algorithm

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Abstract

As there is a rapid growth in healthcare systems and biomedical data. Machine learning algorithms are utilized in many researches for predicting the risk of the diseases. The major intuition of the present paper is to plan for a novel methodology for multi-disease prediction using deep learning. The overall prediction methodology involves several steps such as “(a) Data Acquisition, (b) Optimal Feature selection, (c) Statistical feature Extraction, and (d) prediction”. In the initial step, the medical datasets of diverse diseases is gathered from multiple benchmark sources. Further, the optimal feature selection is applied to the available set of attributes. This is accomplished by hybridizing two meta-heuristic algorithms such as Lion Algorithm (LA), and Butterfly Optimization Algorithm (BOA). In these prediction algorithms, the hidden neuron count of NN and DBN is finely tuned or optimized by the same hybrid Lion-based BOA (L-BOA). The experimental evaluation of various medical datasets validates that the prediction rate of the developed model outperforms several traditional methods.

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Abbreviations

LA:

Lion algorithm

BOA:

Butterfly optimization algorithm

NN:

Neural network

DBN:

Deep belief network

L-BOA:

Lion-based BOA

SVM:

Support vector machine

EMR:

Electronic medical records

MCI:

Mild cognitive impairment

PD:

Parkinson's disease

KNN:

K-nearest neighbor

NB:

Naive Bayesian

EPDP:

Efficient and privacy-preserving disease risk prediction scheme

FPR:

False positive rate

LM:

Linear method

RF:

Random forest

DSAE:

Deep sparse auto-encoder architecture

ESD:

Energy spectral density

HRFLM:

Hybrid random forest with linear model

circRNA:

CircularRibo nucliec acid

FNR:

False negative rate

GIP:

Gaussian interaction profile

GWO:

Grey Wolf optimizer

MCC:

Matthew’s correlation coefficient

FDR:

False discover rate

OU:

Okamoto-Uchiyama

CKD:

Chronic kidney disease

NPV:

Negative predictive value

LDA:

Linear discriminate analysis

DT:

Decision tree

WOA:

Whale optimization algorithm

DBN:

Deep belief network

FRQR:

Fuzzy rough quick reduct

RBM:

Restricted Boltzmann machine

QDA:

Quadratic discriminate analysis

RNN:

Recurrent neural network

CD:

Contrast divergence

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Authors and Affiliations

  1. ABES Engineering College Ghaziabad, Uttar Pradesh, Ghaziabad, 201 009, India

    Anil Kumar Dubey

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  1. Anil Kumar Dubey
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Dubey, A.K. Optimized hybrid learning for multi disease prediction enabled by lion with butterfly optimization algorithm. Sādhanā 46, 63 (2021). https://doi.org/10.1007/s12046-021-01574-8

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