ItemArticle

Implantable Chip Revolutionizing Early-Stage Liver Cancer Detection with Advanced Diagnosis System

Title
Implantable Chip Revolutionizing Early-Stage Liver Cancer Detection with Advanced Diagnosis System
Creator
Sivabalaselvamani, D.; Rajasekaran, N.; Thiyagarajan, D.; Yasotha, S.; Pavithra, N.; Selvakarthi, D.; Hemalatha, S.
Description
Millions of people die from cancer annually. Advanced metastatic cancers may not respond to traditional therapy. The importance for early diagnosis is highlighted by the difficulty of treating cancers in later stages. Enhancing patient outcomes using tissue-engineered cancer diagnosis and therapy is gaining popularity. Cancer and associated immune problems burden healthcare systems, making efficient, high-throughput drug development strategies essential. Thus, implanted chips may solve these issues. A revolutionary technique for early liver cancer identification is the Machine Learning-based Liver Cancer Diagnosis System (ML-LCDS). K-Nearest Neighbour (KNN) identifies liver tumors precisely in ML-LCDS. The performance evaluation reports sensitivity=97.2%, specificity=91.3%, precision=93.5%, FPR=8.7%, and accuracy=94.1%, computed from the confusion matrix derived through 10-fold cross-validation. Experimental findings validate its consistent performance, establishing ML-LCDS as an efficient and reliable diagnostic tool for early-stage liver cancer detection. The Author(s) 2025. The text of this article is open access and licensed under a Creative Commons Attribution 4.0 International License.
Source
International Research Journal of Multidisciplinary Technovation;Volume;7;Issue;6;pp.248-265
Date
01-01-2025
Publisher
Asian Research Association
Subject
Advanced Diagnosis System; Early-Stage Liver Cancer Detection; Healthcare Innovation; Implantable Chip; K-Nearest Neighbour (KNN) Algorithm; Machine Learning-Based Liver Cancer Diagnosis System (ML-LCDS)
Coverage
Sivabalaselvamani D., School of Information Science, Presidency University, Bengaluru, India; Rajasekaran N., Department of Computer Science, Christ (Deemed to be University), Bengaluru, India; Thiyagarajan D., Department of Computer Science and Engineering, Chennai Institute of Technology, Tamil Nadu, Chennai, India; Yasotha S., Department of Computer Science and Engineering, Sri Eshwar College of Engineering, Tamil Nadu, Coimbatore, India; Pavithra N., Department of Information Technology, Jeppiaar Instithute of Technology, Kancheepuram, Tamil Nadu, Sunguvarchatram, India; Selvakarthi D., Department of Electronics and Instrumentation Engineering, Kongu Engineering College, Erode, Tamil Nadu, Perundurai, India; Hemalatha S., Department of Computer Applications, Kongu Engineering College, Erode, Tamil Nadu, Perundurai, India
Rights
All Open Access; Gold Open Access
Relation
ISSN: 25821040;
Format
online
Language
English
Type
Article

Citation

Sivabalaselvamani, D.; Rajasekaran, N.; Thiyagarajan, D.; Yasotha, S.; Pavithra, N.; Selvakarthi, D.; Hemalatha, S., “Implantable Chip Revolutionizing Early-Stage Liver Cancer Detection with Advanced Diagnosis System,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 19, 2026, https://archives.christuniversity.in/items/show/23692.

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