Volume 14, Issue 5

Thyroid Cancer Detection Using Machine Learning

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

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