Volume 14, Issue 5 · IJARST · ISSN 2319-1783 / 2320-1126

Thyroid Cancer Detection Using Machine Learning

Thyroid Cancer Detection Using Machine Learning is an open-access, peer-reviewed research paper by Mayuri Kale 1, Dr. Khusi Sindhi 2, published in Volume 14, Issue 5 of the International Journal of Advanced Research in Science and Technology (IJARST), a UGC-approved journal (Print ISSN 2319-1783, Online ISSN 2320-1126).

Author

Mayuri Kale 1, Dr. Khusi Sindhi 2

Abstract

Thyroid cancer, a growing global health concern, affects the hormone-regulating thyroid gland and has shown a notable increase in incidence due to improved diagnostics and potential environmental factors. Traditional diagnostic methods such as fine needle aspiration (FNA) and ultrasound imaging, while effective, ve limitations including invasiveness, subjectivity, and occasional inconclusive outcomes. This research proposes a machine learning (ML)-based diagnostic system to aid in early and accurate detection of thyroid cancer using clinical and imaging data. By leveraging the power of artificial intelligence (AI), the system aims to support clinicians in distinguishing between benign and malignant nodules, reducing diagnostic errors and improving patient Thyroid cancer impacts a small yet crucial endocrine organ that influences metabolic processes. Although relatively rare, its rising incidence emphasizes the importance of accurate and early diagnosis. Current diagnostic practices are resource-intensive and sometimes unreliable, underscoring the need for technological advancements in healthcare. The integration of ML and AI presents a novel opportunity to improve diagnostic precision and reduce healthcare burdens

DOI

https://doi.org/10.62226/ijarst20252552

PAGES : 1594-1597 | 3 VIEWS | 1 DOWNLOADS

How do you cite this paper?

Mayuri Kale 1, Dr. Khusi Sindhi 2 — “Thyroid Cancer Detection Using Machine Learning.” International Journal of Advanced Research in Science and Technology (IJARST), Volume 14, Issue 5. DOI: https://doi.org/10.62226/ijarst20252552.

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