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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14

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Paper Title: A Comparative Analysis of AI Algorithms for Disease Prediction
Authors Name: Ajmal Jamal , Aniruddh kumar , Alok kumar Patel
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IJRTI_202689
Published Paper Id: IJRTI2504215
Published In: Volume 10 Issue 4, April-2025
DOI:
Abstract: The integration of artificial intelligence (AI) into healthcare has revolutionized disease diagnosis, offering enhanced accuracy, efficiency, and scalability. This paper explores comparison of multi-algorithmic framework for AI-driven disease diagnosis, leveraging diverse machine learning (ML) and deep learning (DL) models to handle a wide range of diagnostic challenges. By employing an ensemble of techniques—including decision trees, support vector machines, neural networks, and convolutional architectures—the study demonstrates how combining algorithms can improve diagnostic precision and robustness across various medical conditions. The paper discusses the comparative performance of these methods on benchmark datasets, outlines the pre-processing and feature engineering techniques essential for clinical data, and highlights real-world applications where such hybrid models are currently deployed. Ethical considerations, data privacy, and the potential for integrating such systems into existing healthcare infrastructure are also examined. Ultimately, this research aims to contribute a comprehensive understanding of how multi-algorithmic strategies can shape the future of intelligent, data-driven disease diagnosis.
Keywords: Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Disease Diagnosis, Multi-Algorithmic Models, Ensemble Learning, Neural Networks, Medical Data Analysis, Diagnostic Systems, Data-Driven Diagnosis
Cite Article: "A Comparative Analysis of AI Algorithms for Disease Prediction", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 4, page no.b923-b928, April-2025, Available :http://www.ijrti.org/papers/IJRTI2504215.pdf
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ISSN: 2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID: IJRTI2504215
Registration ID:202689
Published In: Volume 10 Issue 4, April-2025
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Page No: b923-b928
Country: greater noida, uttar pradesh, India
Research Area: Computer Science & Technology 
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2504215
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2504215
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED, Journal Starting Year (ESTD) : 2016

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