Call for Papers:Vol.10 Issue.6

Submission
Last date		 30-Dec-2024
Acceptance Status In One Day
Paper Publish In Two Days
Submit ManuScript

News & Updates

Submit Article

Dear Authors, Article publish in our journal for Volume-10,Issue-6. For article submission on below link: Submit Manuscript


Join As Board

Dear Reviewer, You can join our Reviewer team without given any charges in our journal. Submit Details on below link: Join As Board


Paper Publication Charges

IJARIIE APP
Download Android App

For Authors

Archives

IJARIIE Board

Downloads

Android App

Download IJARIIE APP

Authors

Title: :  Aniemia detection using machine learning
PaperId: :  23555
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 10 Issue 2 2024
DUI:    16.0415/IJARIIE-23555
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Chaithanya K SDon Bosco Institute of Technology
Deepika M LDon Bosco Institute of Technology
Harshitha MDon Bosco Institute of Technology
Hemavathi SDon Bosco Institute of Technology
Divyashree KDon Bosco Institute of Technology
Yashodara RDon Bosco Institute of Technology

Abstract

Information science and engineering
Anemia, Hemoglobin, MCV, MCH, MCHC, Machine Learning, Logistic regression, K Nearest Classifier, Random Forest, Decision Tree,Artificial neural network.
Computer-aided diagnosis of diseases proves to be a cost- effective solution. In addition to saving time, this approach also ensures accuracy, eliminating for additional manpower in medical decision-making processes. Variousnutrition surveys indicate that nearly a quarter of the global population suffers from anemia. Therefore, there is an urgent need. to develop a proficient machine learning classifier capable of accurately detecting and classifyinganemia. In this study, five ensemble learning methods - Stacking, Bagging, Voting, Adaboost, and Bayesian Boosting- are applied to four classifiers: DT, ANN, Naïve Bayes, and K-Nearest Neighbor. The objective is to identify which individual classifier or combination of classifiers achieves the very best accuracy in classifying blood cells for anemia detection The results demonstrate that among the ensemble methods, the stacking ensemble method attains the highest accuracy. Among the individual classifiers, the ANN performs the best while the K-Nearest Neighbor performs the worst. Interestingly, the combination of T and K-NN, when applied in the Stacking ensemble, achieves substantially better accuracy than the Artificial Neural Network alone. This highlights the reality that an ensemble of classifiers yields superior accuracy as compared to individual classifiers. Therefore, to ensure maximum accuracy in medical decision-making, an ensemble of classifiers should be utilized.

Citations

Copy and paste a formatted citation or use one of the links to import into a bibliography manager and reference.

IJARIIE Chaithanya K S, Deepika M L, Harshitha M, Hemavathi S, Divyashree K, and Yashodara R. "Aniemia detection using machine learning" International Journal Of Advance Research And Innovative Ideas In Education Volume 10 Issue 2 2024 Page 5413-5419
MLA Chaithanya K S, Deepika M L, Harshitha M, Hemavathi S, Divyashree K, and Yashodara R. "Aniemia detection using machine learning." International Journal Of Advance Research And Innovative Ideas In Education 10.2(2024) : 5413-5419.
APA Chaithanya K S, Deepika M L, Harshitha M, Hemavathi S, Divyashree K, & Yashodara R. (2024). Aniemia detection using machine learning. International Journal Of Advance Research And Innovative Ideas In Education, 10(2), 5413-5419.
Chicago Chaithanya K S, Deepika M L, Harshitha M, Hemavathi S, Divyashree K, and Yashodara R. "Aniemia detection using machine learning." International Journal Of Advance Research And Innovative Ideas In Education 10, no. 2 (2024) : 5413-5419.
Oxford Chaithanya K S, Deepika M L, Harshitha M, Hemavathi S, Divyashree K, and Yashodara R. 'Aniemia detection using machine learning', International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 2, 2024, p. 5413-5419. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Aniemia_detection_using_machine_learning_ijariie23555.pdf (Accessed : ).
Harvard Chaithanya K S, Deepika M L, Harshitha M, Hemavathi S, Divyashree K, and Yashodara R. (2024) 'Aniemia detection using machine learning', International Journal Of Advance Research And Innovative Ideas In Education, 10(2), pp. 5413-5419IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Aniemia_detection_using_machine_learning_ijariie23555.pdf (Accessed : )
IEEE Chaithanya K S, Deepika M L, Harshitha M, Hemavathi S, Divyashree K, and Yashodara R, "Aniemia detection using machine learning," International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 2, pp. 5413-5419, Mar-App 2024. [Online]. Available: https://ijariie.com/AdminUploadPdf/Aniemia_detection_using_machine_learning_ijariie23555.pdf [Accessed : ].
Turabian Chaithanya K S, Deepika M L, Harshitha M, Hemavathi S, Divyashree K, and Yashodara R. "Aniemia detection using machine learning." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 10 number 2 ().
Vancouver Chaithanya K S, Deepika M L, Harshitha M, Hemavathi S, Divyashree K, and Yashodara R. Aniemia detection using machine learning. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2024 [Cited : ]; 10(2) : 5413-5419. Available from: https://ijariie.com/AdminUploadPdf/Aniemia_detection_using_machine_learning_ijariie23555.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads



Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
Secure Med: Enhancing Patient Privacy and Care Through BlockchainInformation TechnologyVivek madanlal jaiswal Download
Soil Health ManagementInformation Science and EngineeringDr. Sudheer Shetty Download
5G Technology and its Impact on IoT ApplicationsComputer engineeringEmani Maheswara Reddy Download
REVIEW ON IOT BASED SMART HOME SYSTEMInformation Science and EngineeringNandini Boragave Download
REVIEW PAPER ON 5G NETWORKINGComputer EngineeringMeghana Download
REVIEW PAPER ON CURRENT TECHNOLOGIES,FUTURE DIRECTIONS POLICY IMPLICATION IN AUTOMATIC VEHICLEENGINEERINGChethan H D Download
A Review on Artificial Intelligence in Cyber SecurityInformation Science and Engineering Chandana N M Download
A Review On Internet Of Things (Iot) In HealthcareInformation Science and Engineering Mr. Naveen G Download
An Overview on 3D Printing Technology: Technological, Materials, and ApplicationsInformation Science and EngineeringSannidhi K S Download
A REVIEW PAPER ON TEACHING COMPLEX COMPUTER NETWORK CONCEPTSInformation Science and EngineeringSateesh D S Download
Efficiency and Risks of E-votingMaster of Computer Applicationskartik Download
Artificial Intelligence in Health CareInformation Science and EngineeringM Rihan Download
EXPLORING 5G: CHALLENGES AND SECURITY ISSUES IN CELLULAR TECHNOLOGIESInformation Science And EngineeringAnagha Udupa Y N Download
A COMPARATIVE STUDY ON IPv4 AND IPv6 AND THE IMPLEMENTATION OF IPv6 FOR THE BETTERMENT OF PROTOCOLInformation Science and Engineering Chandana N M Download
A Review on Computer Network Security SystemInformation Science and Engineering Manjunath R Download
12