Predicting Genetic Disorders: Implementation and Deployment on EC2 Instances in AWS

Abstract— Genetic illnesses, caused by DNA mutations— either inherited or acquired—can lead to serious illnesses such as Alzheimer's, cancer, and Hemochromatosis. New developments in artificial intelligence have been promising for early disease detection. In this paper, we address the issue of predicting multiple genetic illnesses by suggesting two primary approaches: (1) a novel feature engineering approach that combines class probabilities from Extra Trees and Random Forest models, and (2) a classifier chain method where predictions from previous models impact subsequent ones. These approaches combined are intended to enhance early and precise detection of genetic conditions. Keywords—genome mutation, genetic disorder, machine learning, chain classifier approach

Authors

Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-04-26
DOI
https://doi.org/10.55041/ijsrem45997
Citations
1
Primary Topic
Imbalanced Data Classification Techniques
Type
article
Field-Weighted Citation Impact
2.48
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article

Predicting Genetic Disorders: Implementation and Deployment on EC2 Instances in AWS

DR M. Prabu
1 citations
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Imbalanced Data Classification Techniques
2.48
article

Predicting Genetic Disorders: Implementation and Deployment on EC2 Instances in AWS

DR M. Prabu
article en
1 citations

Abstract

Abstract— Genetic illnesses, caused by DNA mutations— either inherited or acquired—can lead to serious illnesses such as Alzheimer's, cancer, and Hemochromatosis. New developments in artificial intelligence have been promising for early disease detection. In this paper, we address the issue of predicting multiple genetic illnesses by suggesting two primary approaches: (1) a novel feature engineering approach that combines class probabilities from Extra Trees and Random Forest models, and (2) a classifier chain method where predictions from previous models impact subsequent ones. These approaches combined are intended to enhance early and precise detection of genetic conditions. Keywords—genome mutation, genetic disorder, machine learning, chain classifier approach

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(04)
Openalex Percentile: Top 11%
Imbalanced Data Classification Techniques
2.48
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