Review Paper of Nature-Based Optimization Algorithms for Medicine Predictor

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Hauptverfasser: Janhvi Guha, Anjali Chouksey, Purvi Khodwe, Bhushan V. Inje
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Veröffentlicht: Zenodo 2021
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author Janhvi Guha
Anjali Chouksey
Purvi Khodwe
Bhushan V. Inje
author_facet Janhvi Guha
Anjali Chouksey
Purvi Khodwe
Bhushan V. Inje
contents In comparison to city people, rural residents have less access to healthcare in India. Few competent medical practitioners and healthcare facilities are available in these areas, making them mostly inaccessible to the poor. This problem may be solved by devising a system in which we feed symptoms into an optimization algorithm and return medication names, generic alternative medicines, diagnosis, and a list of nearby hospitals as outputs. This will be extremely beneficial to patients who are experiencing a medical issue. To do so, we identified three algorithms: the Whale Optimization algorithm, the Artificial Bee Colony Optimization algorithm, and the Particle Swarm Optimization algorithm, all of which have high accuracy and could be used with our dataset to provide accurate diagnoses and possible treatments. We also outlined the work's future scope, which includes recognizing crop diseases and anticipating machine maintenance.
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publishDate 2021
publisher Zenodo
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spellingShingle Review Paper of Nature-Based Optimization Algorithms for Medicine Predictor
Janhvi Guha
Anjali Chouksey
Purvi Khodwe
Bhushan V. Inje
Artificial Bee Colony Algorithm
Firefly Algorithm
Nature-based Optimization Algorithms
Particle Swarm Optimization Algorithm
Whale Optimization Algorithm
In comparison to city people, rural residents have less access to healthcare in India. Few competent medical practitioners and healthcare facilities are available in these areas, making them mostly inaccessible to the poor. This problem may be solved by devising a system in which we feed symptoms into an optimization algorithm and return medication names, generic alternative medicines, diagnosis, and a list of nearby hospitals as outputs. This will be extremely beneficial to patients who are experiencing a medical issue. To do so, we identified three algorithms: the Whale Optimization algorithm, the Artificial Bee Colony Optimization algorithm, and the Particle Swarm Optimization algorithm, all of which have high accuracy and could be used with our dataset to provide accurate diagnoses and possible treatments. We also outlined the work's future scope, which includes recognizing crop diseases and anticipating machine maintenance.
title Review Paper of Nature-Based Optimization Algorithms for Medicine Predictor
topic Artificial Bee Colony Algorithm
Firefly Algorithm
Nature-based Optimization Algorithms
Particle Swarm Optimization Algorithm
Whale Optimization Algorithm
url https://doi.org/10.5281/zenodo.18514888