Volume 2, Issue 8

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This issue presents a research paper about using computer programs called machine learning algorithms to help detect cancer early. The study tested 19 different algorithms to see how well they could spot cervical cancer from medical data. The researchers made sure their approach could work for many types of cancer, not just cervical cancer. They found that some algorithms were very good at finding cancer quickly and accurately. This research is important because cancer is a major health problem worldwide, and finding it early can save lives. The study’s findings could help doctors use these computer programs to detect different types of cancer more effectively in the future, potentially improving patient care and outcomes.

Editorial
Editorial
1 Page, 4,520 KB Download PDF
Front Cover

Journal of Engineering Research and Sciences, Volume 2, Issue 8, Page # i–i, 2023

Editorial
1 Page, 703 KB Download PDF
Editorial Board

Journal of Engineering Research and Sciences, Volume 2, Issue 8, Page # ii–ii, 2023

Editorial
1 Page, 650 KB Download PDF
Editorial

by Paul Andrew

Journal of Engineering Research and Sciences, Volume 2, Issue 8, Page # iii–iii, 2023

Editorial
1 Page, 654 KB Download PDF
Table of Contents

Journal of Engineering Research and Sciences, Volume 2, Issue 8, Page # iv–iv, 2023

Articles
Open AccessArticle
18 Pages, 3,413 KB Download PDF
Imputation and Hyperparameter Optimization in Cancer Diagnosis

by Yi Liu, Wendy Wang and Haibo Wang
Journal of Engineering Research and Sciences, Volume 2, Issue 8, Page # 1-18, 2023; DOI: 10.55708/js0208001
Abstract: Cancer is one of the leading causes for death worldwide. Accurate and timely detection of cancer can save lives. As more machine learning algorithms and approaches have been applied in cancer diagnosis, there has been a need to analyze their performance. This study has compared the detection accuracy and speed of nineteen machine learning algorithms… Read More

(This article belongs to the Special Issue on SP3 (Special Issue on Multidisciplinary Sciences and Advanced Technology 2023) and the Section Medical Informatics (MDI))

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