## 4 Discussion  
FNA biopsy is a widely accepted technique for detecting nontoxic thyroid nodules. Evaluation and management of thyroid nodules with classification systems aims to triage patients who need surgery and then follow the surgical procedures appropriate for their disease [31]. In addition, due to uncertain cytological properties, FNA biopsy of a thyroid nodule is limited mainly to distinguishing between malignant or benign follicular neoplasms, follicular variants of papillary cancer, hyperplastic nodules, and Hurthle cells [32,33]. It should always be remembered that the results of an FNA biopsy are nondiagnostic, suspicious, or uncertain in 20-30% of cases [32]. Conventional clinical treatment for indeterminate aspirates is a repeated FNA biopsy; however, 38-48% uncertainty still exists even if IAA is repeated. Diagnostic surgery, which causes high cost and difficulties for the patient, can be applied [33]. In most cancer cases, there is only one nodule in the group. Yet, relevant literature reported no significant relationship between the number of nodules and [34]. Most of the community of scientists working on the subject think that the increase in the number of nodules does not affect the risk of malignancy [35]. Previous studies, including meta-analyses, compared US imaging and the results of FNA biopsies of thyroid nodules by US imaging criteria for the diagnosis of malignancy, including microcalcification, hypoecheogenicity, a long axis perpendicular to the skin, and poorly defined (irregular, lobulated) borders [36, 37, 38]. Consistent with previous studies, we determined that the sonographic features of thyroid nodules, such as calcification pattern (microcalcification), contour features (irregular, lobulated), cervical lymph node involvement, echogenicity (significant hypoecheogenicity/hypoechogenicity), and aspect ratio (taller than wide) were the strongest predictors of malignancy. One of the features that makes this study different from other studies is that the specificity of the evaluation of lymph nodes is high since each of the sonographic examinations is assumed to be of equal importance. Evaluation of cervical lymph nodes, which is a part of thyroid sonography, is deemed essential to detect any metastasis. Microcalcification in ipsilateral pathological lymph nodes, hypoecheogenicity in their cortex, and an increase in cortex thickness and vascularization are significant regarding metastasis in malignant thyroid nodules [39, 40, 41]. This study presents widespread US properties regarding the hypoechoic halo, including thyroid nodules, capsule, contour, aspect ratio, shape, size, echogenicity, calcification pattern, color Doppler vascularity, internal composition, and the status of cervical lymph node. Another study found that if US imaging features are used to detect nodules, more efficient results can be obtained than nodule size. In line with this information, the researchers concluded that more studies are needed on the malignancy analysis of nodules in the thyroid [42]. Also in this study, it was determined that the malignancy was not affected by the size of the nodule. This study includes a comparison of four different machine learning methods that evaluate thyroid nodules. Overall, across machine learning algorithms, J48 DT, which is a nonlinear machine learning algorithm, gave the best results compared to the other three machine learning methods. In addition to its successful results, its ease of use, reproducibility, and cost-effectiveness may encourage the use of this algorithm in the diagnosis of malignant tumors. Besides, it may conveniently be used to reveal excessive treatment and unnecessary operations that cause a significant financial burden on SSI.