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Comparison of Implementation in Blood Cancer Causes and Diseases

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Comparison of Implementation in Blood Cancer Causes and Diseases


Tripti R Kulkarni | Bharathi Gururaj | Aditi Jaiswal



Tripti R Kulkarni | Bharathi Gururaj | Aditi Jaiswal "Comparison of Implementation in Blood Cancer Causes and Diseases" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-9 | Issue-1, February 2025, pp.503-512, URL: https://www.ijtsrd.com/papers/ijtsrd73869.pdf

Blood malignancies are extremely dangerous for human life. Early and accurate detection is essential for efficient treatment and improved patient outcomes. Traditional diagnostic methods can be subjective and time-consuming. Delays in diagnosis can lead to life-threatening complications, as some blood cancers progress rapidly. This work explores the transformative potential of Machine Learning (ML) and Deep Learning (DL) in blood cancer detection. Support Vector Machine (SVM) and other machine learning methods and K Nearest Neighbour (KNN) analyze blood cell images and identify cancerous cell features, achieving high accuracy in leukemia detection. This allows for faster and more objective diagnoses, potentially leading to earlier interventions and improved patient outcomes. Deep Learning approaches, particularly Convolutional Neural Networks (CNNs), hold even greater promise. The requirement for manual feature extraction is eliminated by CNNs' ability to automatically learn features from images. The integration of ML and DL significantly improves blood cancer detection accuracy and efficiency. This paves the way for earlier diagnoses, improved patient care, and ultimately, saving lives. This work concludes by pointing forth possible directions for more study, such as improving these methods even more.

cancer, machine learning, convolution neural network


IJTSRD73869
Volume-9 | Issue-1, February 2025
503-512
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

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