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Enhancing Cancer Detection With Machine Learning: Development of a Model Using Ibm Cloud Technology

Year: 2025

Type: article

Abstract: Cancer early detection is vital and has become a major research area for health and computing research. The collaboration between the two fields is essential as more efficient algorithms in machine learning is required. This paper is a demonstration of cancer detection using the IBM machine learning cloud in which different algorithms has been embedded. The Breast Cancer Wisconsin (Diagnostic) Dataset (WDBC) consisting of trained and untrained is used for the analysis. The result shows high rate of accuracy in detecting cancer. The results can also be viewed in different format, thereby making the IBM machine learning cloud an effective means of achieving a comprehensive simulation

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.14892678

Authors: Chikezie, Emmanuel Okoro, Linda Ngozi, Adebayo

Institutions: Ignatius Ajuru University of Education, University of Africa Toru-Orua

Language: English

Topic: Artificial Intelligence in Healthcare

Subfield: Health Information Management

Field: Health Professions

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W6911738410

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