Modeling a Logistic Regression based Sustained Approach for Cancer Detection

Title

Modeling a Logistic Regression based Sustained Approach for Cancer Detection

Creator

Pattanaik A.; Gour P.; Mishra S.; Sharma V.; Alabdeli H.

Description

This assessment and treatment of cancer may be done using logistic regression. To properly forecast whether a tumour is malignant or benign, the likelihood of binary outcomes may be simulated based on input variables and taken into account for factors like volume, topology and texture. It aids in risk assessment by estimating an individual's likelihood of developing cancer using factors like age-group, relatives past data, life choices and gene based markers. Logistic regression plays an important role in early cancer detection and creating screening tools that identify high-risk individuals through patent characteristics, biomarkers, and medical imaging data. Prediction of the probability of survival based on age, tumor characteristics, treatment options and comorbidities is useful for survival analysis. In a comparative study, logistic regression achieved a high accuracy of 97.4%, along with random forest, in cancer detection and diagnosis. 2023 IEEE.

Source

International Conference for Technological Engineering and its Applications in Sustainable Development, ICTEASD 2023, pp. 262-267.

Date

2023-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Binary outcome; Cancer detection; Cancer diagnosis; Logistic regression; Survival analysis; Tumour classification

Coverage

Pattanaik A., KIIT Deemed to Be University, School of Computer Engineering, Odisha, Bhubaneswar, 751024, India; Gour P., KIIT Deemed to Be University, School of Computer Engineering, Odisha, Bhubaneswar, 751024, India; Mishra S., KIIT Deemed to Be University, School of Computer Engineering, Odisha, Bhubaneswar, 751024, India; Sharma V., CHRIST (Deemed to Be University), Computer Science Department, Delhi NCR, India; Alabdeli H., The Islamic University, College of Technical Engineering, Najaf, Iraq

Rights

Restricted Access

Relation

ISBN: 979-835033647-4

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ICTEASD57136.2023.10585150

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199558340&doi=10.1109%2fICTEASD57136.2023.10585150&partnerID=40&md5=23b6ffa81d9583339c094ac207820e51